An evaluation method and device for hydrogen safety of a fuel cell vehicle

Abstract

The present invention relates to the field of hydrogen safety technology, and more specifically, to a method and device for assessing the hydrogen safety of fuel cell vehicles. The method comprises: collecting raw data from fuel cell vehicles; constructing a system comprising multiple hydrogen safety assessment indicators; calculating the current hydrogen safety level of the fuel cell vehicle based on the raw data and the hydrogen safety assessment indicators; determining active safety intervention measures for the fuel cell vehicle based on the hydrogen safety level, and evaluating the active safety intervention measures. This invention can effectively improve the hydrogen safety level of fuel cell vehicles and ensure the safe operation of fuel cell vehicles.

Description

Technical Field

[0001] The present invention relates to the field of hydrogen safety technology, and in particular to a method and device for evaluating hydrogen safety of a fuel cell vehicle. Background Art

[0002] With increasing environmental protection requirements and adjustments to energy structures, fuel cell vehicles (FCVs), as a new type of clean energy vehicle, are attracting increasing attention. However, due to the flammable and explosive nature of hydrogen, hydrogen safety issues have become a key factor restricting the development of FCVs. Therefore, a comprehensive assessment of hydrogen safety in FCVs is crucial for ensuring their safe operation.

[0003] In view of this, the present invention is proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and device for evaluating the hydrogen safety of a fuel cell vehicle, so as to comprehensively evaluate the hydrogen safety level of a fuel cell vehicle.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for evaluating hydrogen safety of a fuel cell vehicle, comprising:

[0007] Collecting raw data of fuel cell vehicles, including fuel cell internal microstructure safety parameters, hydrogen storage system data, hydrogen supply system data, fuel cell system data, vehicle operation data, and environmental interaction dynamic parameters;

[0008] Constructing a system that includes multiple hydrogen safety assessment indicators, including micro-electrochemical parameter indicators, hydrogen leakage risk indicators, hydrogen combustion and explosion risk indicators, hydrogen system reliability indicators, personnel safety risk indicators, and environmental safety risk indicators;

[0009] Calculate the hydrogen safety level of the current fuel cell vehicle based on the raw data and hydrogen safety assessment indicators;

[0010] Active safety intervention measures for the fuel cell vehicle are determined according to the hydrogen safety level, and the active safety intervention measures are evaluated.

[0011] In a second aspect, the present invention provides an electronic device, comprising:

[0012] at least one processor, and a memory communicatively coupled to the at least one processor;

[0013] The memory stores instructions that can be executed by at least one of the processors. The instructions are executed by at least one of the processors to enable the at least one processor to execute the above-mentioned fuel cell vehicle hydrogen safety assessment method.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] The comprehensive hydrogen safety assessment method and equipment for fuel cell vehicles of the present invention collect original data on the hydrogen safety of fuel cell vehicles, establish a hydrogen safety assessment index system, use an artificial intelligence algorithm to build a hydrogen safety evaluation model, conduct a comprehensive assessment of the hydrogen safety of fuel cell vehicles, and propose corresponding safety measures and suggestions based on the assessment results. This can effectively improve the hydrogen safety level of fuel cell vehicles and ensure the safe operation of fuel cell vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 1 is a flow chart of a method for evaluating hydrogen safety of fuel cell vehicles provided by an embodiment of the present invention;

[0018] Figure 2 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0019] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0020] Figure 1 This is a flow chart of a method for evaluating hydrogen safety in fuel cell vehicles provided by this embodiment. This embodiment is applicable to the situation where the hydrogen safety level of fuel cell vehicles is scientifically and rationally evaluated. This method can be executed by an electronic device. Figure 1 , the method provided in this embodiment includes the following operations:

[0021] S110. Collect original data of the fuel cell vehicle.

[0022] The original data includes fuel cell internal microstructure safety parameters, hydrogen storage system data, hydrogen supply system data, fuel cell system data, vehicle operation data and environmental interaction dynamic parameter data.

[0023] Fuel cell internal microstructural safety parameters include the relationship between changes in the microscopic pores of the proton exchange membrane and hydrogen permeation, and the impact of the degree of electrode catalyst particle agglomeration on hydrogen reaction efficiency and safety. These parameters are regularly monitored using specialized microscopic inspection techniques (such as high-resolution electron microscopy and atomic force microscopy).

[0024] The method for obtaining microscopic pore changes in proton exchange membranes uses high-resolution transmission electron microscopy (TEM): with a resolution of 0.1nm, it can observe the distribution, size (such as 1-100nm micropores) and connectivity of nanoscale pores in the membrane. Sampling is done regularly (such as after every 500 hours of operation), and the membrane is frozen and sliced (50-100nm thick). After TEM imaging, the pore parameters are calculated using ImageJ software; the method for obtaining hydrogen permeation is in situ electrochemical impedance spectroscopy (EIS), which indirectly reflects pore connectivity through changes in membrane resistance (increase in pores → decrease in resistance → increase in H2 permeation). For example, after a commercial vehicle fuel cell stack (80kW) has been running for 1000 hours, TEM shows that the membrane pore density has increased from 50 / μm² to 180 / μm², and the average pore size has increased from 15nm to 32nm, corresponding to a hydrogen permeability increase from 2.5×10 -8 Increased to 8.7×10 -8 mol·m -1 ·s -1 ·Pa -1 , verifying the positive correlation between pore changes and hydrogen permeation.

[0025] When a fuel cell vehicle is running, multiple reference electrodes can be arranged in the fuel cell stack to monitor the potential distribution of each single cell in real time. By observing local potential anomalies, possible problems can be inferred. Alternatively, the interaction between infrared light and material molecules can be used to analyze the absorption spectrum to detect the concentration of reaction gas, the generation of intermediate products, etc., to determine the reaction state and microstructural changes on the electrode surface. Temperature sensors, pressure sensors, humidity sensors, etc. can also be arranged at the pipe positions in the fuel cell stack to monitor parameter changes in real time. If local overheating occurs, it may indicate uneven porosity of the motor and poor gas diffusion; if the gas pressure changes, it may indicate whether the bipolar plate flow channel is blocked; if the humidity is abnormal, it may affect the proton conductivity of the electrolyte membrane, etc. By monitoring the changes in these parameters, a hydrogen safety evaluation subsystem based on changes in microscopic physical structure can be constructed.

[0026] Hydrogen storage system data includes: hydrogen pressure, temperature, flow rate, leakage rate, capacity, sealing status, and safety interlocks. Hydrogen supply system data includes: pressure, flow rate, humidity, and temperature. Fuel cell system data includes: fuel cell output power. Vehicle operation data includes: vehicle speed. Environmental interaction dynamic parameters include: ambient temperature and humidity.

[0027] Optionally, after collecting the raw data, preprocess it to remove outliers and noise to ensure data accuracy and reliability. Data preprocessing can be performed using methods such as data filtering and outlier detection. For example, the 3σ principle or box plot method can be used to handle outliers.

[0028] This embodiment preferably considers dynamic parameters of environmental interaction, focusing on dynamic parameters closely related to hydrogen safety in complex and changing vehicle environments. In addition to common environmental factors such as temperature and humidity, the chemical effects of atmospheric pollutants (such as sulfur dioxide and nitrogen oxides) on hydrogen storage and fuel cell reactions are studied in depth and quantified as evaluation indicators (i.e., environmental safety risk indicators).

[0029] S120. Build a system that includes multiple hydrogen safety assessment indicators.

[0030] Hydrogen safety assessment indicators include microelectrochemical parameter indicators, hydrogen leakage risk indicators, hydrogen combustion and explosion risk indicators, hydrogen system reliability indicators, personnel safety risk indicators, and environmental safety risk indicators. Each indicator is described in detail below.

[0031] Microscopic electrochemical parameter indicators include proton exchange membrane porosity (ΔPEM_porosity) and catalyst agglomeration index (CI_catalyst).

[0032] The proton exchange membrane porosity is derived from high-resolution electron microscopy (HR-TEM) images (e.g., number of pores per 100 μm² membrane area / area). For example, if the initial pore area is 0.5 μm² and increases to 1.2 μm² (for a membrane area of 100 μm²) after 1000 hours of operation, then ΔPEM_porosity = 0.7%. Proton exchange membranes require replacement when the porosity exceeds 2% (corresponding to a hydrogen permeation rate exceeding 0.1 NL / min). Catalyst agglomeration index data is derived from atomic force microscopy (AFM) 3D morphology and particle size distribution statistics.

[0033] Hydrogen leakage risk indicators include leakage probability (P_leak) and leakage rate (Q_leak). The leakage rate uses the formula provided by the revised version of the national standard GB / T 34542.5-2022 (including the impact of pollutants). The leakage probability is derived based on a seal aging model (coupled with PM2.5 clogging of micropores). This model accounts for factors such as sealing material aging, environmental conditions (such as temperature and pressure), and time.

[0034] The hydrogen explosion risk index is used to quantify the hazardous consequences of hydrogen explosions, including explosion overpressure and ignition probability. The explosion overpressure (ΔP_explosion) is calculated using the TNT equivalent method (considering a hydrogen cloud concentration > 4% explosion limit). For example, if the leak volume W_H2 = 1kg and the distance r = 5m, then ΔP_explosion = 20kPa (ΔP_explosion > 10kPa is the threshold for rupturing the human eardrum). The ignition probability (P_ignition) is based on environmental factors (corrected for static electricity and contaminant conductivity):

[0035] P_ignition=0.1+0.005·[NO x ] (NOx unit: ppm, experimental statistics);

[0036] For example: NO x =50ppm, P_ignition=0.35 (35% ignition risk).

[0037] Hydrogen system reliability indicators are used to quantify failure frequency, including system reliability (R_system) and mean time between failures (MTBF). System reliability (R_system) can be calculated using a fault tree analysis (FTA). For example, after 1000 hours of operation, R_system = 77.8% (below the safety threshold of 80%, requiring maintenance). MTBF is calculated using a modified Arrhenius model (coupled with pollutant concentrations). For example, if temperature = 80°C and SO2 = 10 ppm, MTBF = 4500 hours (baseline value 5000 hours).

[0038] Personnel safety risk indicators are used to quantify individual harm, including hydrogen exposure dose (D_exposure) and evacuation time (T_evac). D_exposure is calculated using a time-weighted average (TWA) algorithm. For example, if a hydrogen concentration of 8% persists for 10 minutes after a leak, D_exposure = 8% × 10 = 80%·min (>50%·min poses a risk of coma). Evacuation time (T_evac) varies based on pollutant concentrations. For example, if PM2.5 concentration is 200 μg / m³, T_evac = 2.2 minutes (exceeding the available safety time by 2 minutes requires an alert escalation).

[0039] Environmental safety risk indicators are used to quantify the ecological impact of hydrogen leaks, including hydrogen diffusion concentration (C_H2_env) and pollutant coupling risk (R_env). The pollutant coupling risk (R_env) should consider the combined toxicity of hydrogen and other pollutants. For example, if the combined toxicity is greater than 1, an environmental emergency response is required.

[0040] S130. Calculate the hydrogen safety level of the current fuel cell vehicle based on the original data and the hydrogen safety assessment index.

[0041] Optionally, the values of each hydrogen safety assessment indicator are first calculated based on the raw data, and the values of these indicators are normalized to facilitate subsequent calculations. For example, a weighted average of the indicator values is performed based on the weight of each hydrogen safety assessment indicator. The sum of these values (which may be referred to as the comprehensive hydrogen safety assessment value) is used to determine the hydrogen safety level of the current fuel cell vehicle. For example, based on the comprehensive hydrogen safety assessment value, the hydrogen safety status of fuel cell vehicles is classified into five levels: safe, relatively safe, generally safe, relatively unsafe, and unsafe. The criteria for grading each level are determined based on actual circumstances.

[0042] S140. Determine active safety intervention measures for the fuel cell vehicle based on the hydrogen safety level, and evaluate the active safety intervention measures.

[0043] When a vehicle's hydrogen safety level is different, the vehicle will take different active safety intervention measures, such as ventilation, decompression, and isolation, to ensure the safety of the vehicle. This embodiment innovatively evaluates active safety intervention measures to improve the hydrogen safety level of fuel cell vehicles. Hydrogen safety evaluation is closely integrated with active safety intervention measures to form a closed-loop safety assurance system. For example, when the hydrogen safety level is relatively unsafe or unsafe, the risk of hydrogen leakage is considered to be increased, and the effectiveness and timeliness of the intervention measures such as ventilation, decompression, and isolation taken by the vehicle are evaluated.

[0044] The following details how to evaluate proactive safety interventions.

[0045] First, we constructed evaluation metrics for the intervention measures, including: hydrogen concentration reduction index, pressure relief device response time, pressure regulation accuracy, personnel evacuation efficiency, fire extinguishing effectiveness, and hydrogen system emergency shutdown reliability. The following details the calculation process for each intervention measure evaluation metric.

[0046] Hydrogen concentration reduction index: the extent to which the hydrogen concentration decreases within a specified time after the vehicle is ventilated.

[0047] Response time of the pressure reducing device: the time from when the hydrogen safety indicator is detected to be less safe or unsafe to when the pressure reducing device opens.

[0048] Pressure regulation accuracy: the minimum unit of pressure regulation of a pressure reducing device.

[0049] On fuel cell vehicles, the actual extent of the reduction in hydrogen concentration within a specified time after vehicle ventilation, the actual response time of the pressure reducing device, and the actual pressure regulation accuracy are calculated to obtain the values of the aforementioned indicators.

[0050] The calculated index value is compared with the benchmark threshold required by the index. If the benchmark threshold requirement is met, it means that the vehicle's active safety intervention measures meet the hydrogen safety requirements.

[0051] Optionally, in addition to evaluating the active intervention measures of the vehicle, the present invention also evaluates the protection of personnel by the active intervention measures and the reliability of the hydrogen safety system.

[0052] For example, using virtual reality or digital twin technology to simulate the hydrogen accident process of a fuel cell vehicle (including hydrogen leakage and personnel evacuation) includes the following steps:

[0053] 1. Build a digital twin model and virtual reality engine. The digital twin model includes a millimeter-level 3D scene, integrating the vehicle's hydrogen system, Matlab / Simulink (for system control), Fluent (for fluid simulation), the vehicle's current emergency response measures (including the time to trigger the isolation zone, window and door opening, hydrogen system shutdown measures, etc.), and AnyLogic (for personnel evacuation). The virtual reality engine, including Unity / Unreal, renders an immersive environment, tracking human movement and using an eye tracker to capture decision-making focus.

[0054] 2. Data acquisition sensors (hydrogen concentration, temperature, valve status) within the vehicle and the surrounding environment are connected to the digital twin model, with an update frequency of 100Hz. Historical accident data (such as a 2023 hydrogen refueling station leak) is injected into the digital twin model to calibrate model parameters. Human behavior data (such as panic index) is simulated using virtual reality in the digital twin model's virtual layer and fed into the digital twin model via a Python interface.

[0055] 3. Verification and iteration, including:

[0056] Physical experiment calibration: Conduct small-scale leak-fire experiments in the hydrogen safety laboratory and compare the experimental data with the simulated data of the digital twin model (including original data and personnel behavior, etc.). The error should be less than 15%;

[0057] Closed-loop optimization: Operational errors discovered during VR training (e.g., 30% of trainees ignoring the risk of secondary leakage) are fed back to the digital twin model to update the current vehicle's emergency response measures.

[0058] Through the above methods, virtual reality / digital twins can not only simulate the process of hydrogen accidents involving fuel cell vehicles, but also detect design defects in advance (such as insufficient width of evacuation channels) and optimize emergency plans (such as prioritizing regional isolation rather than shutting down the entire station), ultimately achieving predictive protection of hydrogen safety.

[0059] During the simulated hydrogen accident, the evacuation efficiency, fire extinguishing effectiveness, and reliability of the hydrogen system's emergency shutdown were determined. Specifically, evacuation efficiency was determined based on the evacuation time, speed, and orderliness of the evacuation; fire extinguishing effectiveness was determined by fire extinguishing time, fire spread control, and key area protection; and the reliability of the hydrogen system's emergency shutdown was determined by the hydrogen system's shutdown response time, shutdown success rate, and false shutdown rate.

[0060] The efficiency of personnel evacuation includes: evacuation time (i.e. the total time from the alarm sounding when the accident occurs to the evacuation of all personnel), evacuation speed (i.e. the number of people or distance evacuated per unit time), and evacuation orderliness (i.e. the behavior and order of personnel during the evacuation process, which can be quantified using an orderliness index with a value of 0-1, the closer to 1, the more orderly).

[0061] The fire extinguishing effect includes: fire extinguishing time (i.e. the time from the occurrence of fire to the time when the fire is completely controlled or extinguished), fire spread control (i.e. comparing the spread range at different time points with the spread range when no intervention measures are taken, and calculating the control rate) and key parts protection (i.e. the protection of important locations such as fuel cell systems and key vehicle components during the simulation process, as well as the assessment of the degree of damage).

[0062] The reliability of the hydrogen system's emergency shutdown includes: shutdown response time (i.e., the time from triggering the emergency shutdown command to the fuel cell system stopping working), shutdown success rate (i.e., the ratio of the number of successful emergency shutdowns to the total number of simulations in multiple simulations), and false shutdown rate (i.e., the ratio of the number of shutdowns that should not be triggered in the simulation to the total number of simulations) to evaluate the emergency shutdown reliability.

[0063] Optionally, after evaluating the active safety intervention measures, optimization suggestions are made based on the evaluation results of the active safety intervention measures.

[0064] For example, if evacuation efficiency, fire extinguishing effectiveness, or the reliability of the hydrogen system's emergency shutdown fails to meet safety requirements, targeted optimization suggestions will be provided for the areas that fail to meet safety requirements. For example, if evacuation efficiency fails to meet safety requirements, optimizations can be made in vehicle design, personnel training, and emergency response systems. If fire extinguishing effectiveness fails to meet safety requirements, optimizations can be made in firefighting facilities, firefighting strategies, and monitoring and early warning systems. If emergency shutdown reliability fails to meet safety requirements, optimizations can be made in system design, safety mechanisms, and testing and maintenance. These optimizations are fed back into the digital twin model and virtual reality, and the hydrogen accident process is re-simulated. The effectiveness of the optimization suggestions is evaluated by comparing the values of the hydrogen safety assessment indicators and the intervention measure evaluation indicators from the two simulations. If the optimization results in significant improvements in both the hydrogen safety assessment indicators and the intervention measure evaluation indicators, such as a faster rate of hydrogen concentration reduction and a shorter fire extinguishing time, the optimization suggestion is considered effective. This embodiment provides a unique evaluation perspective for improving the response capabilities of hydrogen fuel cell vehicles in the event of an accident.

[0065] Optionally, when calculating the current fuel cell vehicle's hydrogen safety level based on the raw data and hydrogen safety assessment indicators, this embodiment utilizes an artificial intelligence algorithm to construct a hydrogen safety assessment model. Such algorithms, such as a deep belief network (DBN) or a generative adversarial network (GAN), are used to construct the hydrogen safety assessment model. Unlike traditional evaluation methods based on the analytic hierarchy process (AHP) and cloud models, the hydrogen safety assessment model can integrate multiple types of data (i.e., the values of hydrogen safety assessment indicators) and further incorporate visual status data of key vehicle components acquired through image recognition technology (e.g., whether the hydrogen tank shell exhibits deformation or signs of corrosion). Through the deep integration and learning of multimodal data, the hydrogen safety assessment model can automatically uncover hidden associations and potential risk patterns between the data, deriving a comprehensive hydrogen safety assessment value, and then, based on the magnitude of the value, determining the current fuel cell vehicle's hydrogen safety level.

[0066] The comprehensive hydrogen safety assessment method and equipment for fuel cell vehicles of the present invention collect original data on the hydrogen safety of fuel cell vehicles, establish a hydrogen safety assessment index system, use an artificial intelligence algorithm to build a hydrogen safety evaluation model, conduct a comprehensive assessment of the hydrogen safety of fuel cell vehicles, and propose corresponding safety measures and suggestions based on the assessment results. This can effectively improve the hydrogen safety level of fuel cell vehicles and ensure the safe operation of fuel cell vehicles.

[0067] like Figure 2As shown, this embodiment provides an electronic device, including:

[0068] at least one processor; and

[0069] a memory communicatively connected to at least one of the processors; wherein,

[0070] The memory stores instructions executable by at least one processor, and the instructions are executed by at least one processor to enable at least one processor to perform the above method. At least one processor in the electronic device is capable of performing the above method, thereby having at least the same advantages as the above method.

[0071] Optionally, the electronic device also includes interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of a GUI (Graphical User Interface) on an external input / output device (such as a display device coupled to the interface). In other embodiments, if necessary, multiple processors can be used with multiple memories, and / or multiple buses can be used with multiple memories. Similarly, multiple electronic devices can be connected (for example, as a server array, a group of blade servers, or a multi-processor system), with each device providing part of the necessary operations. Figure 2 A processor 301 is taken as an example.

[0072] Memory 302, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the fuel cell vehicle hydrogen safety assessment method in the embodiments of the present invention. Processor 301 executes the software programs, instructions, and modules stored in memory 302 to perform various functional applications and data processing of the device, thereby implementing the aforementioned fuel cell vehicle hydrogen safety assessment method.

[0073] The memory 302 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data created based on the use of the terminal, etc. Furthermore, the memory 302 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 302 may further include a memory remotely located relative to the processor 301, and these remote memories may be connected to the device via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0074] The electronic device may further include: an input device 303 and an output device 304. The processor 301, the memory 302, the input device 303 and the output device 304 may be connected via a bus or other means. Figure 2 The bus connection is taken as an example.

[0075] The input device 303 can receive input digital or character information, and the output device 304 can include a display device, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0076] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved. This is not limited herein.

[0077] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for evaluating hydrogen safety of fuel cell vehicles, characterized in that: include: Collecting raw data of fuel cell vehicles, including fuel cell internal microstructure safety parameters, hydrogen storage system data, hydrogen supply system data, fuel cell system data, vehicle operation data, and environmental interaction dynamic parameters; Constructing a system that includes multiple hydrogen safety assessment indicators, including micro-electrochemical parameter indicators, hydrogen leakage risk indicators, hydrogen combustion and explosion risk indicators, hydrogen system reliability indicators, personnel safety risk indicators, and environmental safety risk indicators; Calculate the hydrogen safety level of the current fuel cell vehicle based on the raw data and hydrogen safety assessment indicators; Determining active safety intervention measures for the fuel cell vehicle based on the hydrogen safety level and evaluating the active safety intervention measures, including: Use virtual reality or digital twin technology to simulate the hydrogen accident process of the fuel cell vehicle, and determine the efficiency of personnel evacuation, fire extinguishing effect and reliability of emergency shutdown of the hydrogen system during the hydrogen accident; wherein, construct a digital twin model and a virtual reality engine, the digital twin model includes a millimeter-level three-dimensional scene, integrating the vehicle hydrogen system, system control, fluid simulation, current vehicle emergency measures, and personnel evacuation model; the virtual reality engine includes rendering an immersive environment, tracking human body movements, and capturing decision focus with an eye tracker; the data acquisition sensors in the vehicle and the environment are connected to the digital twin model, and in the digital twin Historical accident data is injected into the model to calibrate the model parameters; virtual reality is used in the virtual layer of the digital twin model to simulate personnel behavior data and pass it into the digital twin model; active safety intervention measures are evaluated based on the personnel evacuation efficiency, fire extinguishing effect and reliability of the hydrogen system emergency shutdown, among which the personnel evacuation efficiency is determined according to the evacuation time, evacuation speed and evacuation orderliness during the accident; the fire extinguishing effect is determined by the fire extinguishing time, fire spread control and protection of key parts; the reliability of the hydrogen system emergency shutdown is determined by the hydrogen system shutdown response time, shutdown success rate and false shutdown rate.

2. The method according to claim 1, characterized in that The active safety interventions described include ventilation, decompression, and isolation.

3. The method according to claim 1, characterized in that Evaluate the proactive safety interventions, including: Constructing intervention measure evaluation indicators, including hydrogen concentration reduction index, pressure relief device response time, pressure regulation accuracy, personnel evacuation efficiency, fire extinguishing effect, and reliability of hydrogen system emergency shutdown; Active safety intervention measures are evaluated according to the intervention measure evaluation indicators.

4. The method according to claim 3, characterized in that Evaluate proactive safety interventions based on the intervention evaluation indicators, including: Under the active safety intervention measures of the fuel cell vehicle, calculating the hydrogen concentration reduction index, the response speed of the pressure reducing device and the pressure regulation accuracy; Active safety intervention measures are evaluated based on the hydrogen concentration reduction index, the response speed of the pressure reducing device and the pressure regulation accuracy.

5. The method according to claim 1, wherein Following the evaluation of the proactive safety interventions, the following also applies: Propose optimization suggestions based on the evaluation results of proactive safety intervention measures; After optimization, virtual reality or digital twin technology is used again to simulate the hydrogen accident process of the fuel cell vehicle, and the effectiveness of the optimization suggestions is evaluated.

6. An electronic device, characterized in that: include: at least one processor, and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to execute the method for evaluating hydrogen safety of a fuel cell vehicle according to any one of claims 1 to 5.

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