Hydrogen leakage risk monitoring system and method for fuel cell generator car

Abstract

The invention relates to a hydrogen leakage risk monitoring system and method for a fuel cell generator car, the system comprises a sensor module installed in a carriage, and a simulation module, a risk assessment module and an alarm module which are installed in a cockpit, the sensor module is used for collecting hydrogen concentration and position information; the collected information is transmitted to the simulation module; the simulation module is used for simulating a hydrogen leakage process and outputting a hydrogen quality evolution simulation result to the danger evaluation module; and the risk assessment module is used for calculating a risk range and a safety distance and transmitting the risk range and the safety distance to the alarm module for display and early warning prompt. Compared with the prior art, through the synergistic effect of the sensor module, the simulation module and the evaluation module, whole-process monitoring and quantitative risk prediction of hydrogen leakage are realized, and potential risks caused by hydrogen leakage can be identified in advance and effectively warned, so that the use safety of fuel cell vehicle-mounted hydrogen is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen leakage detection, and more particularly to a hydrogen leakage risk monitoring system and method for a fuel cell power generation vehicle. Background Art

[0002] Hydrogen, as a clean energy source, is widely used in fuel cell vehicles. However, its flammable and explosive characteristics make hydrogen leakage a potential safety hazard. Traditional hydrogen leakage detection mainly focuses on post-leakage treatment measures, lacking effective leakage volume detection, risk assessment, and quantitative prediction schemes, resulting in serious consequences of leakage accidents and being unfavorable for improving the safety of hydrogen use.

[0003] To solve the above problems, existing research determines whether hydrogen leakage occurs by real-time detecting the hydrogen concentration in the vehicle. For example, Chinese Patent CN118538962A obtains the hydrogen output of the vehicle's hydrogen storage system; obtains the hydrogen input of the vehicle's fuel cell system; obtains the hydrogen consumption of the fuel cell system; and then determines whether there is hydrogen leakage in the vehicle by comparing at least two of the hydrogen output of the hydrogen storage system, the hydrogen input of the fuel cell system, and the hydrogen consumption of the fuel cell system through threshold comparison. However, this method that simply relies on hydrogen concentration detection and threshold comparison cannot accurately quantify the leakage risk, that is, it cannot identify and effectively warn of the potential risks caused by hydrogen leakage in advance, and users cannot know the specific situation of the leakage. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned defects existing in the prior art and provide a hydrogen leakage risk monitoring system and method for a fuel cell power generation vehicle, which can realize the whole-process monitoring of hydrogen leakage and quantitative risk prediction.

[0005] The purpose of the present invention can be achieved by the following technical solutions: A hydrogen leakage risk monitoring system for a fuel cell power generation vehicle includes a sensor module installed in the carriage and a simulation module, a risk assessment module, and an alarm module installed in the cockpit. The sensor module is used to collect hydrogen concentration and position information and transmit the collected information to the simulation module;

[0006] The simulation module is used to simulate the hydrogen leakage process and output the simulation result of hydrogen mass evolution to the risk assessment module;

[0007] The risk assessment module is used to calculate the risk range and safety distance and transmit them to the alarm module for display and warning prompts.

[0008] Further, the alarm module includes an in-vehicle display and an audible and visual alarm.

[0009] A method for monitoring hydrogen leakage risk of a fuel cell power generation vehicle, comprising the following steps:

[0010] S1. Construct a Fluent model of the fuel cell vehicle to simulate the hydrogen leakage process;

[0011] S2. Real-time collect the hydrogen concentration data inside the vehicle, and perform simulation calculations in combination with the Fluent model of the fuel cell vehicle to obtain the hydrogen mass evolution result;

[0012] S3. Based on the hydrogen mass evolution result, determine the risk range and safety distance through equivalent TNT mass calculation, and perform corresponding display and warning prompts.

[0013] Further, the specific process of step S1 is as follows:

[0014] Establish a geometric model and simplify it, and perform mesh division processing on the simplified geometric model;

[0015] Establish a diffusion equation, and set boundary conditions and the external environment.

[0016] Further, the geometric model includes a hydrogen storage geometric structure and a hydrogen transmission geometric structure.

[0017] Further, the diffusion equation includes:

[0018] Continuity equation, i.e., mass conservation equation:

[0019]

[0020] Momentum equation:

[0021]

[0022] Energy equation:

[0023]

[0024] Component transport equation:

[0025]

[0026] where u x 、u y 、u z are the velocity components in the X, Y, and Z directions respectively, t is time, ρ is the density of the fluid, p is the fluid pressure, τ xx ,τ yy ,τ zz are the components of the viscous stress τ, f x 、f y 、f zThey are the body forces per unit mass in the X, Y, and Z directions respectively. E is the total energy of the fluid particle, including internal energy, kinetic energy, and potential energy, and k eff is the effective heat transfer coefficient, and h j is the enthalpy of component j, and J j is the diffusion flux of component j.

[0027] Furthermore, the process of setting the boundary conditions is as follows: Select the failure of the pipeline valve as the leakage scenario, and set the leakage port type as the mass flow inlet;

[0028] For the wall boundary condition in the boundary conditions, set the surfaces of the cab, chassis, and hydrogen storage bottles as the Wall wall condition;

[0029] Take the lower surface of the calculation space as the ground, and similarly ignore the influence of the ground temperature and roughness, and set it as the Wall wall condition;

[0030] All the Wall wall boundaries are set as smooth non-slip walls, and the standard wall function is used for calculation.

[0031] Furthermore, the setting of the external environment includes environmental temperature, exhaust air intensity, and external flow field.

[0032] Furthermore, the specific process of step S2 is as follows: Obtain the hydrogen concentration data, dynamically start the hydrogen cloud diffusion simulation calculation, generate the diffusion distribution map of the cloud in space, and construct an accurate diffusion model based on the hydrogen concentration diffusion rate, leakage amount, environmental wind speed, temperature and humidity parameters, and simulate the diffusion and evolution process of hydrogen in the air. During the simulation process, comprehensively consider fluid dynamics, gas diffusion equations, and turbulence effects, and output the cloud diffusion range and the distribution results of the dangerous area in the form of high-resolution visualization.

[0033] Furthermore, the specific process of step S3 is as follows: Substitute the simulation data into the equivalent TNT model, and calculate the dangerous radius of the explosion, determine the minimum safety distance and the explosion risk range according to the leakage amount and concentration change of hydrogen, the volume and mass of the hydrogen combustible cloud. Among them, the dangerous radius includes the death radius, the serious injury radius, and the minor injury radius, specifically:

[0034]

[0035] Among them, R1 is the death radius, R2 is the serious injury radius, R3 is the minor injury radius, and W TNT is the equivalent mass of TNT, Q TNT is the explosion energy per unit mass of TNT explosive, P0 is the overpressure, α is the explosion efficiency coefficient of the combustible vapor cloud, that is, the mass of the combustible gas participating in the explosion, A is the ground explosion coefficient, and W f is the hydrogen mass, Q f is the heat of combustion of hydrogen;

[0036] The minimum safety distance is 1.5 times the dangerous radius, and the explosion risk range is the spherical range corresponding to 1.5 times the dangerous radius.

[0037] Compared with the prior art, the present invention has the following advantages:

[0038] The present invention installs a sensor module in the carriage, and installs a simulation module, a risk assessment module and an alarm module in the cockpit. The sensor module is used to collect the hydrogen concentration and position information, and transmit the collected information to the simulation module; the simulation module is used to simulate the hydrogen leakage process and output the simulation result of the hydrogen mass evolution to the risk assessment module; the risk assessment module is used to calculate the risk range and safety distance, and transmit them to the alarm module for display and early warning. Thus, through the coordinated action of the three modules of sensor, simulation and assessment, the whole process monitoring of hydrogen leakage and quantitative risk prediction are realized, and the potential risks caused by hydrogen leakage can be identified in advance and effectively warned, so as to effectively improve the safety of on-vehicle hydrogen use in fuel cell vehicles.

[0039] In the computer simulation platform of the present invention, a Fluent simulation model inside the fuel cell vehicle is established for the diffusion simulation of hydrogen leakage. By establishing a geometric model, simplifying it and performing grid division, while retaining most of the structural details of the vehicle, the body and its various components are simplified, which can not only ensure the reliability of the simulation results, but also reduce the geometric complexity of the model, thereby shortening the calculation time and contributing to the convergence of the results. By establishing a diffusion equation and setting boundary conditions and external environment, the process of hydrogen leaking at a constant slow speed and diffusing in space can be truly and effectively simulated, ensuring the accuracy of subsequent simulation results.

[0040] Based on the hydrogen mass evolution results obtained by simulation, the present invention calculates the equivalent TNT mass and the dangerous radius to determine the risk range and safety distance, which can facilitate users to know the quantified risk level and perform corresponding operation processing in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the system result of the present invention;

[0042] Figure 2 It is a schematic diagram of the method flow of the present invention;

[0043] Figure 3 It is a schematic diagram of the application process of the embodiment;

[0044] Figure 4 It is a flowchart for constructing the Fluent model of the fuel cell vehicle

[0045] Figure 5Structural diagram of a fuel cell vehicle in the embodiment;

[0046] Figure 6 Structural diagram of a fuel cell vehicle model in the embodiment;

[0047] Figure 7 Fluent calculation grid diagram in the embodiment;

[0048] Figure 8 Equivalent TNT calculation flow chart;

[0049] Explanation of the markings in the figure: 1. Sensor module, 2. Simulation module, 3. Hazard assessment module, 4. Alarm module. Detailed implementation manners

[0050] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] Embodiment

[0052] A hydrogen leakage risk monitoring system for a fuel cell power generation vehicle includes a sensor module 1 installed in the carriage and a simulation module 2, a hazard assessment module 3, and an alarm module 4 installed in the cockpit. Among them, the sensor module 1 is used to collect hydrogen concentration and position information and transmit the collected information to the simulation module 2;

[0053] The simulation module 2 is used to simulate the hydrogen leakage process and output the simulation result of the hydrogen mass evolution to the hazard assessment module 3;

[0054] The hazard assessment module 3 is used to calculate the risk range and safety distance and transmit them to the alarm module 4 for display and early warning prompts.

[0055] Among them, the alarm module 4 includes an in-vehicle display and an audible and visual alarm.

[0056] Based on the above system, a hydrogen leakage risk monitoring method for a fuel cell power generation vehicle is realized. As Figure 2 shown, it includes the following steps:

[0057] S1. Construct a Fluent model of the fuel cell vehicle to simulate the hydrogen leakage process;

[0058] S2. Real-time collect the hydrogen concentration data in the vehicle and perform simulation calculations in combination with the Fluent model of the fuel cell vehicle to obtain the hydrogen mass evolution result;

[0059] S3. Based on the hydrogen mass evolution result, determine the risk range and safety distance through equivalent TNT mass calculation, and perform corresponding display and early warning prompts.

[0060] This embodiment applies the above scheme, and the main process is as Figure 3 shown:

[0061] 1. The sensor module sends the leakage location and the hydrogen leakage amount to the simulation module according to the value of the hydrogen leakage amount monitored by the hydrogen sensor installed in the fuel cell power generation vehicle.

[0062] 2. The simulation module inputs the received location information and hydrogen leakage amount into the Fluent simulation model of the fuel cell power generation vehicle, simulates and emulates the leakage, and takes the evolution result of the hydrogen mass as the output and inputs it into the risk assessment module.

[0063] 3. The risk assessment module adopts the equivalent TNT explosion equivalent method, calculates the possible explosion hazard radius and hazard area according to the cloud concentration and volume of the leaked hydrogen. Combining the actual hydrogen concentration information and leakage amount, it quickly calculates the explosion range. Based on the obtained hazard radius and the hydrogen concentration monitored by the sensor, it conducts a comprehensive assessment, gives different risk levels, and outputs them to the in-vehicle display.

[0064] Specifically, first, a Fluent model of the fuel cell vehicle is constructed. In this embodiment, in the computer simulation platform, a Fluent simulation model inside the fuel cell vehicle is established. The process of constructing the Fluent model is as Figure 4 shown. It is used for the diffusion simulation of hydrogen leakage. In the Fluent simulation model, it is necessary to accurately define the hydrogen storage and transmission parts inside the vehicle, including the geometric structures of components such as hydrogen storage tanks and fuel cell stacks.

[0065] At the leakage orifice, the gas velocity is equal to the local speed of sound. However, its pressure is still higher than the surrounding atmospheric pressure. Therefore, after flowing out of the leakage orifice, the air flow will continue to expand and accelerate, resulting in a supersonic air flow. For supersonic flow, the mass flow rate of hydrogen is calculated as:

[0066]

[0067] In the formula, C d is the leakage coefficient. When the leakage orifice is circular, it takes 1; A is the area of the leakage orifice; p0 and p are the ambient pressure and the initial pressure of the gas leakage respectively; R is the universal gas constant, taking 8.314 J / (mol·K); T is the gas temperature; M is the molar mass of hydrogen, taking 0.002 kg / mol; k is the adiabatic index, taking 1.4.

[0068] The entire gas diffusion process follows the mass, momentum, and energy conservation equations;

[0069] The continuity equation, i.e., the mass conservation equation:

[0070]

[0071] The momentum equation:

[0072]

[0073] Energy equation:

[0074]

[0075] Component transport equation:

[0076]

[0077] In the above formulas, u x 、u y 、u z are the velocity components in the X, Y, and Z directions respectively, t is the time, ρ is the density of the fluid, p is the fluid pressure, τ xx , τ yy , τ zz are the components of the viscous stress τ, f x 、f y 、f z are the body forces per unit mass in the X, Y, and Z directions respectively, E is the total energy of the fluid particle, including internal energy, kinetic energy, and potential energy, k eff is the effective heat transfer coefficient, h j is the enthalpy of component j, J j is the diffusion flux of component j.

[0078] This embodiment studies a hydrogen fuel cell vehicle as a mobile emergency power supply vehicle, and the design structure is as shown in Figure 5 . In order to perform numerical simulation more efficiently on the Fluent platform, the Spaceclaim software is used to simplify the vehicle body and its various components while retaining most of the structural details of the vehicle. This can not only ensure the reliability of the simulation results but also reduce the geometric complexity of the model, thereby shortening the calculation time and facilitating the convergence of the results. The simplified vehicle body and flow field model are as shown in Figure 6 .

[0079] When using Fluent for fluid calculations, reasonable mesh generation is crucial for ensuring simulation accuracy, calculation stability, and efficiency. Fine meshes can accurately capture the flow characteristics in complex geometric regions, such as boundary layers, turbulent core regions, and high-gradient regions, reducing numerical errors and improving the description accuracy of physical phenomena. At the same time, optimized mesh generation can improve iterative convergence and avoid unstable fluctuations in calculations. In addition, by locally refining key regions and simplifying the mesh density in secondary regions, it is possible to ensure the reliability of the simulation results while significantly reducing the consumption of computing resources. This method of balancing accuracy and efficiency is a key strategy in the simulation of complex fluid problems. The mesh generation used in the simulation software in this embodiment is as shown in Figure 7 .

[0080] Finally, the boundary conditions are set. In this embodiment, the typical leakage scenario of pipeline valve failure is selected. To simulate the process of hydrogen leaking at a constant slow speed and diffusing in space under the condition of valve failure and reflect the actual situation, the leakage port type is set as a mass flow inlet in this embodiment. For the wall boundary conditions in the boundary conditions, the cab, chassis, and hydrogen storage cylinder will all block hydrogen. On the premise of not considering the influence of materials and surface roughness, their respective surfaces are set as the Wall wall conditions. In addition, the lower surface of the calculation space is used as the ground. Similarly, ignoring the influence of ground temperature and roughness, it is also set as the Wall wall condition. These Wall wall boundaries are all set as smooth non-slip walls and calculated using the standard wall function.

[0081] Then, according to the specific scenario, set the environmental temperature, exhaust air intensity, and model the external flow field, and then the calculation can start. During the calculation, an appropriate residual needs to be selected. When the iterative residual is less than the set residual value, it can be considered that the calculation converges, and thus reliable results can be obtained.

[0082] After that, arrange monitoring sensors and set the leakage points. In the hydrogen leakage monitoring, the arrangement of sensors should meet the requirements of comprehensive coverage and rapid response to leakage characteristics and flow field dynamics to accurately capture the concentration distribution and spatio-temporal variation law of the leaked hydrogen. First of all, the sensors should be arranged near the possible leakage points, as well as the dominant direction of flow field diffusion and high-concentration accumulation areas to ensure real-time monitoring of the concentration changes in key areas. Secondly, the sensor spacing should be reasonably set according to the diffusion characteristics of the leaked gas, avoiding redundancy caused by over-density and missing the rapid changes in local high concentrations due to over-rarity. Finally, the sensors should have high sensitivity and rapid response capabilities and be installed at fixed positions that do not interfere with the flow field characteristics to ensure the accuracy and reliability of the data, providing timely and accurate basic data for subsequent safety assessment and control.

[0083] To meet the above requirements, 12 sensors are placed near the hydrogen cylinder rack, and the arrangement of the sensors is as Figure 1 shown to capture any possible leakage situation. When the hydrogen sensors detect leakage, they will upload the leakage amount data to the simulation module.

[0084] Then, conduct simulation of the leakage cloud diffusion. The simulation module dynamically initiates the hydrogen cloud diffusion simulation calculation by obtaining the real-time feedback of hydrogen concentration data from sensors, and generates the diffusion distribution map of the cloud in space. Based on key parameters such as the hydrogen concentration diffusion rate, leakage volume, environmental wind speed, temperature and humidity, etc., this module constructs an accurate diffusion model to simulate the diffusion and evolution process of hydrogen in the air. During the simulation process, the module comprehensively considers fluid dynamics, gas diffusion equations and turbulence effects, and outputs the cloud diffusion range and the distribution results of dangerous areas in a high-resolution visualization form. Finally, these simulation results are transmitted to the risk assessment module in real time for calculating potential risk areas, evaluating accident consequences, and providing data support for emergency decision-making.

[0085] Finally, calculate the explosion range based on the equivalent TNT method. As Figure 8 shown, the risk assessment module substitutes the simulation data into the equivalent TNT model, and quickly calculates the dangerous radius of the explosion according to the leakage volume and concentration change of hydrogen, and generates the data of the explosion impact area, and transmits the calculation result to the alarm module.

[0086] The calculation formula for the explosion of the TNT equivalent vapor cloud is:

[0087]

[0088] Where W TNT is the equivalent mass of TNT, kg; α is the explosion efficiency coefficient of the combustible vapor cloud, that is, the mass of the combustible gas participating in the explosion; A is the ground explosion coefficient, which is 1.8 when the explosion occurs on the ground surface; W f is the hydrogen mass, kg; Q f is the combustion heat of hydrogen, 1.43×10 5 kJ / kg; Q TNT is the explosion energy per unit mass of TNT explosive, 4.52×10 3 kJ / kg.

[0089] The hazards caused by the explosion include the degree of harm to personnel and the degree of damage to building facilities. The degree of human injury can divide the injury area into a death area, a serious injury area and a minor injury area. The corresponding death radius R1 represents the death radius caused by head impact or lung injury, where the peak value of the shock wave reaches 241.3 kPa; the serious injury radius R2 refers to the radius area corresponding to a 50% probability of eardrum rupture, and the shock wave overpressure range is between 34.5 - 48.3 kPa; the minor injury radius R3 refers to the eardrum rupture radius caused by the shock wave overpressure, with a probability of 1%, and the shock wave overpressure range is 13.8 kPa. This study will calculate the overpressure injury and the minimum safety distance according to the volume and mass of the hydrogen combustible cloud in the confined space under different scenarios. The calculation formula for the dangerous radius is as follows:

[0090]

[0091] After calculating the dangerous radius, the minimum safety distance is 1.5 times the dangerous radius, and the explosion risk range is the spherical range corresponding to 1.5 times the dangerous radius.

[0092] Based on the output of the risk assessment module, the alarm module will display the explosion risk range and safety distance on the in-vehicle display in real time to help the vehicle driver quickly judge whether there is danger. The alarm module will also give an audible and visual warning to enhance the driver's safety awareness.

[0093] In summary, this solution proposes a real-time risk assessment solution applicable to on-vehicle hydrogen leakage, especially suitable for quantitative risk prediction of hydrogen leakage accidents in fuel cell power generation vehicles. This solution can provide efficient prediction of the explosion dangerous radius and improve the safety of hydrogen use through an alarm mechanism.

Claims

1. A hydrogen leakage risk monitoring system for a fuel cell power generation vehicle, characterized in that: It comprises a sensor module (1) installed in a vehicle compartment, a simulation module (2) installed in a cockpit, a risk assessment module (3) and an alarm module (4), wherein the sensor module (1) is used to collect hydrogen concentration and position information, and transmit the collected information to the simulation module (2); The simulation module (2) is used to simulate the hydrogen leakage process and output the simulation result of hydrogen mass evolution to the risk assessment module (3); The risk assessment module (3) is used to calculate the risk range and safety distance, and transmit them to the alarm module (4) for display and early warning.

2. A hydrogen leakage risk monitoring system for a fuel cell power generation vehicle according to claim 1, characterized in that: The alarm module (4) comprises a vehicle-mounted display and an audible and visual alarm.

3. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle, characterized in that: The following steps are involved: S1. Build a Fluent model of a fuel cell vehicle to simulate the hydrogen leakage process; S2. Real-time collection of hydrogen concentration data in the vehicle, and simulation calculation combined with the Fluent model of the fuel cell vehicle to obtain the hydrogen mass evolution results; S3. Based on the evolution of hydrogen mass, the risk range and safety distance are determined through equivalent TNT mass calculation, and corresponding displays and warning prompts are given.

4. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 3, characterized in that: The specific process of step S1 is as follows: Establishing and simplifying the geometric model, and performing meshing processing on the simplified geometric model; Establish the diffusion equation and set the boundary conditions and external environment.

5. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 4, characterized in that: The geometric model includes a hydrogen storage geometry and a hydrogen transmission geometry.

6. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 4, characterized in that: The diffusion equation includes: The continuity equation is the mass conservation equation: Momentum equation: Energy equation: Component transport equation: Among them, u x 、u y 、u z are the velocity components in the X, Y, and Z directions, t is time, ρ is the density of the fluid, p is the fluid pressure, τ xx , τ yy , τ zz is the component of viscous stress τ, f x 、f y 、f z are the unit mass forces in the X, Y, and Z directions respectively, E is the total energy of the fluid microgroup, including internal energy, kinetic energy, and potential energy, k eff is the effective heat transfer coefficient, h j is the enthalpy of component j, J j is the diffusion flux of component j.

7. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 4, characterized in that: The process of setting the boundary conditions is as follows: selecting pipeline valve failure as the leakage scenario, and setting the leakage port type to mass flow inlet; For the wall boundary conditions in the boundary conditions, the surfaces of the cab, chassis and hydrogen storage tank are set as Wall wall conditions; The lower surface of the calculation space is taken as the ground, and the influence of ground temperature and roughness is also ignored, and it is set as the Wall surface condition; The Wall boundaries are all set as smooth no-slip walls, and the standard wall function is used for calculation.

8. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 4, characterized in that: The settings of the external environment include ambient temperature, exhaust intensity, and external flow field.

9. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 3, characterized in that: The specific process of step S2 is: obtaining hydrogen concentration data, dynamically starting hydrogen cloud diffusion simulation calculation, generating a diffusion distribution map of the cloud in space, building an accurate diffusion model based on hydrogen concentration diffusion rate, leakage volume, ambient wind speed, temperature and humidity parameters, simulating the diffusion and evolution process of hydrogen in the air, and in the simulation process, comprehensively considering fluid dynamics, gas diffusion equations and turbulence effects, and outputting the cloud diffusion range and dangerous area distribution results in a high-resolution visual form.

10. A method for monitoring hydrogen leakage risk for a fuel cell power generation vehicle according to claim 9, characterized in that: The specific process of step S3 is: bring the simulation data into the equivalent TNT model, calculate the explosion danger radius according to the leakage amount and concentration change of hydrogen, the volume and mass of the hydrogen combustible cloud, determine the minimum safety distance and the explosion risk range, wherein the danger radius includes the death radius, the serious injury radius and the minor injury radius, specifically: Among them, R1 is the death radius, R2 is the serious injury radius, R3 is the light injury radius, and W TNT is the equivalent mass of TNT, Q TNT is the explosion energy per unit mass of TNT explosives, P0 is the overpressure, α is the explosion efficiency coefficient of the combustible vapor cloud, that is, the mass of the combustible gas involved in the explosion, A is the ground explosion coefficient, W f is the mass of hydrogen, Q f is the heat of combustion of hydrogen; The minimum safety distance is 1.5 times the danger radius, and the explosion risk range is the spherical range corresponding to 1.5 times the danger radius.

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