A simulation method for the fusion model of arcing process and post-arcing process of mechanical switch

Abstract

The present invention discloses a simulation method for a fusion model of the arc burning process and the post-arc process of a mechanical switch. The present invention summarizes the physical characteristics of the arc, such as the arc definition, the arc volt-ampere characteristics, the arc temperature and the energy balance of the arc, determines the arc model using the magnetohydrodynamic model as the simulation, and corrects and simplifies the MHD equation group according to the actual arc model and the quantitative polar relationship between the physical quantities in the equation, thereby obtaining a corrected and simplified arc MHD model. The simulation of the arc burning process of the DC switch arc at different frequencies is realized in the finite element simulation software, and the CTM calculates the parameters of the sheath growth process in combination with the influence of the arc burning process, and finally obtains the influence of the frequency on the post-arc sheath growth process. It reflects the breaking process of the DC mechanical switch in the moving and static contacts, which is of great significance for studying the arc burning characteristics of the DC circuit breaker and the breaking capacity of the switch at different breaking current frequencies.

Description

Technical Field

[0001] The present invention relates to the technical field of DC circuit breaker breaking, and in particular to a simulation method for a fusion model of an arcing process and a post-arc process of a mechanical switch. Background Art

[0002] In recent years, extensive research work has involved various arc suppression technologies, including but not limited to gas-insulated circuit breakers, vacuum circuit breakers, magnetically controlled circuit breakers, etc. The application of these technologies aims to improve the efficiency and controllability of DC circuit breakers when interrupting current. In addition, material science and circuit breaker design optimization also provide strong support for improving the performance of DC circuit breakers.

[0003] The study of arcing characteristics of DC circuit breakers is of key significance to many fields. In high-voltage DC transmission systems, the performance of DC circuit breakers directly affects the efficiency of power transmission and the stability of the system. In the field of industrial automation, DC circuit breakers are used to control various electric equipment, and their performance is closely related to the continuity and reliability of the production process.

[0004] The study of arcing characteristics of DC circuit breakers has always been a cutting-edge topic in the field of power systems, with significant engineering and scientific value. With the vigorous development of renewable energy and the widespread application of high-voltage DC transmission systems, DC power systems have become a key component of the contemporary power industry. However, as a key component of the power system, the arc phenomenon generated by DC circuit breakers when interrupting current poses a severe challenge to the safety and reliability of the power system.

[0005] The study of arcing characteristics of DC circuit breakers involves many complex factors, including the thermodynamic behavior of the arc, the dynamic characteristics of the arc, the stability of the arc, the release mechanism of the arc energy, the control of the arc length, the temperature distribution of the arc, and the arc extinguishing process. These factors are directly related to the performance and life of the circuit breaker and the stable operation of the power system. Therefore, in-depth research on the arcing characteristics of DC circuit breakers is crucial to improving the reliability and safety of the power system. Summary of the invention

[0006] In view of the above problems and technical requirements, the present invention proposes a simulation method for the fusion model of the arc burning process and the post-arc process of a mechanical switch, summarizes the physical characteristics of the arc such as arc definition, arc volt-ampere characteristics, arc temperature and arc energy balance, determines the arc model with the magnetohydrodynamic model as the simulation, and corrects and simplifies the MHD equation group according to the actual arc model and the quantitative polar relationship between the physical quantities in the equation, thereby obtaining the corrected and simplified arc MHD model. Using the two-dimensional axisymmetric arc MHD model, combined with the setting of plasma physical parameters and boundary conditions and the grid division of the calculation area, the simulation of the arc burning process of the DC switch arc at different frequencies is realized in the finite element simulation software, and the CTM combines the influence of the arc burning process to calculate the parameters of the sheath growth process, and finally obtains the influence of frequency on the post-arc sheath growth process.

[0007] In order to achieve the above object, the present invention adopts the following technical scheme:

[0008] A simulation method for a fusion model of arcing process and post-arcing process of a mechanical switch, comprising the following steps:

[0009] Step 1, establish a two-dimensional axisymmetric mechanical switch model;

[0010] Step 2: In order to facilitate the convergence of simulation calculations and reduce the complexity of simulation, several assumptions are introduced during the simulation process to constrain the mechanical switch model;

[0011] Step 3, combining the actual situation of arc plasma to form a set of magnetohydrodynamic equations that conform to the characteristics of arc plasma;

[0012] Step 4, boundary condition setting: select the flow field, thermal field, electric field, magnetic field and fluid particle tracking modules according to the magnetic fluid dynamic model, and select the dynamic grid module for simulation of the opening and closing action of the mechanical switch simulation model;

[0013] Step 5, combining the actual situation of the mechanical switch model operation, perform user-defined grid division;

[0014] Step 6, based on the particle motion simulation results obtained by the magnetic fluid dynamic model, the continuous transition model is used in combination with the influence of the arcing process to calculate the parameters of the sheath growth process, obtain the influence of frequency on the post-arc sheath growth process, and determine the breaking capacity of the mechanical switch.

[0015] Furthermore, the constraint conditions in step 2 are:

[0016] (1) Assume that the arc plasma to be solved is an equilibrium plasma, that is, it satisfies the local thermodynamic equilibrium state;

[0017] (2) Assuming that the arc plasma is axisymmetric, the flow of the arc plasma generated by the electromagnetic force is laminar;

[0018] (3) The density, electrical conductivity, thermal conductivity, constant-pressure heat capacity, and dynamic viscosity coefficient of arc plasma are only functions of temperature.

[0019] Furthermore, the magnetohydrodynamic equations in step 3 include: mass conservation equation, radial momentum conservation equation, axial momentum conservation equation, energy conservation equation, current continuity equation, Maxwell's equations, and Ohm's law.

[0020] Furthermore, the boundary conditions in step 4 are set as:

[0021] The magnetofluid dynamic model selects the flow field, thermal field, electric field, magnetic field and fluid particle tracking modules for setting, and the movement of the contact adopts the dynamic mesh operation; the objects that need to be set include the dynamic and static electrodes, fluid domain, central axis and moving mesh.

[0022] Furthermore, the user-defined grid division in step 5 includes dividing the grid of the fluid domain into fine, where the fine definition is: the grid size parameter range is 0.025-0.875 mm; dividing the boundary grid of the electrode into finer, where the finer definition is the grid size parameter range is 0.01-0.7 mm.

[0023] Furthermore, the criterion of the continuous transition model in step 6 is: comparing the product of the neutral metal vapor particle and the sheath length with the Baschen curve to determine the breaking capacity of the mechanical switch.

[0024] The beneficial effects of the present invention are as follows:

[0025] (1) The present invention simplifies the basic theoretical model and applies it to the dynamic process of mechanical switch disconnection, which is conducive to the study of mechanical switch stress;

[0026] (2) The present invention simulates the dynamic process of opening and closing of a mechanical switch in a DC circuit breaker. The simulation results can reflect the arcing characteristics during the opening and closing of the switch, such as electrical signal characteristics such as current and voltage, as well as temperature field and magnetic field characteristics;

[0027] (3) The present invention performs model calculation simulation on the post-arc process in the DC circuit breaker, and can obtain the breaking limit of the mechanical switch under different breaking current frequencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a two-dimensional axisymmetric model of the mechanical switch of the present invention.

[0029] Figure 2 This is a diagram showing the setting of boundary conditions constrained by the control equations of the present invention.

[0030] Figure 3 This is a user-defined setting diagram for the mesh division of the present invention.

[0031] Figure 4a , Figure 4b , Figure 4c , Figure 4d , Figure 4e , Figure 4f It is the transient results of the current density and voltage signal of the DC interruption of the present invention and the temperature and conductivity of the mechanical switch interruption process; wherein, Figure 4a is the arcing voltage signal diagram, Figure 4b is the arc current density signal diagram, Figure 4c This is the arc temperature space cloud diagram at 0.1ms. Figure 4d Figure 4e shows the arc temperature space cloud diagram at 3.45ms, and Figure 4e shows the arc conductivity space cloud diagram at 0.1ms. Figure 4f This is the spatial cloud diagram of arc conductivity at 3.45ms.

[0032] Figure 5 This is a graph showing the relationship between the instantaneous and delayed restrike voltages and the neutral metal vapor density and sheath length. DETAILED DESCRIPTION

[0033] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0034] A mechanical switch arcing process and post-arc process fusion model simulation method of the present invention comprises the following steps:

[0035] Step 1, establish a two-dimensional axisymmetric mechanical switch model;

[0036] Step 2: In order to facilitate the convergence of simulation calculations and reduce the complexity of simulation, some assumptions are introduced in the simulation process to constrain the mechanical switch model and obtain constraint conditions;

[0037] Step 3, combining the actual situation of arc plasma to form a set of magnetohydrodynamic equations that conform to the characteristics of arc plasma;

[0038] Step 4, the boundary conditions of the model are set by selecting the flow field, thermal field, electric field, magnetic field and fluid particle tracking modules according to the magnetohydrodynamic model (MHD) model, and the dynamic grid module is selected for simulation of the opening and closing action of the mechanical switch simulation model;

[0039] Step 5: Perform user-defined meshing in the simulation based on the actual operation of the mechanical switch model.

[0040] Step 6: Based on the motion simulation results of the particles obtained by MHD, the continuous transition model (CTM) is used to combine the influence of the arcing process to calculate the parameters of the sheath growth process. Finally, the influence of frequency on the post-arc sheath growth process is obtained to determine the breaking capacity of the mechanical switch.

[0041] Specifically, the constraints in step 2 are:

[0042] (1) Assume that the arc plasma to be solved is an equilibrium plasma, that is, it satisfies the local thermodynamic equilibrium state;

[0043] (2) Assuming that the arc plasma is axisymmetric, the flow of the arc plasma generated by the electromagnetic force is laminar;

[0044] (3) The density, electrical conductivity, thermal conductivity, constant-pressure heat capacity, and dynamic viscosity coefficient of arc plasma are only functions of temperature;

[0045] (4) The influence of arc on contact ablation and near-pole sheath is ignored in the simulation.

[0046] Specifically, the magnetohydrodynamic equations in step 3 are:

[0047] The mass conservation equation:

[0048]

[0049] Radial momentum conservation equation:

[0050]

[0051] Axial momentum conservation equation:

[0052]

[0053] Energy conservation equation:

[0054]

[0055] Current continuity equation:

[0056]

[0057] Maxwell's equations:

[0058]

[0059] Ohm's Law:

[0060]

[0061]

[0062] In equations (1) to (4), t is time, r is radial distance, z is height, h is heat transfer coefficient, ρ is density, η is dynamic viscosity coefficient, and c is p is the constant pressure heat capacity, k is the thermal conductivity, σ is the electrical conductivity, P is the plasma pressure, v r is the radial velocity, v z is the axial velocity, and T is the temperature. The four parameters ρ, η, cp, and k are all nonlinear functions of temperature. r 、v z , T are four basic variables. B =1.38×10 -23 J.K. -1 is the Boltzmann constant, and e is the charge of the electron. z B θ and j r B θ is the Lorentz force term, the left side of the equation in equation (4) is the convection term, and the right side of the equation is, from left to right, the Joule heat term (the main reason for the arc rise), the radiation term, the thermal conductivity term, the thermal conductivity term, and the electron enthalpy transport term caused by electron drift, where the radiation term is represented by the net radiation source term built into the software. (5) In the equation, σ is the conductivity, V is the potential, and (6) in the equation, μ 0 =4π×10 -7 H·m -1 is the vacuum magnetic permeability. In equations (2) to (4), the current density j r 、j z 、Self-induced magnetic field B θ Use equations (6) and (7) to find out.

[0063] The partial differential equations composed of equations (1) to (7) are used for simulation calculations. The above equations can be used to solve the flow field, temperature, electric field and magnetic field of the plasma. The calculation results are related to the selection of boundary conditions and plasma parameters (conductivity, thermal conductivity, constant pressure heat capacity, dynamic viscosity coefficient, density).

[0064] Specifically, the boundary conditions in step 4 are set as:

[0065] The MHD model selects five modules for setting: flow field, thermal field, electric field, magnetic field, and fluid particle tracking. The movement of the contact uses dynamic mesh operation. Objects that need to be set include dynamic and static electrodes, fluid domains, central axes, and other physical field boundaries.

[0066] Specifically, the user-defined grid division in step 5 includes:

[0067] The number, quality, refinement and density distribution of the grid all have a crucial impact on the convergence of the solved equations. Any slight defect in the grid will affect the calculation process, resulting in non-convergence of the results and the inability to complete the simulation calculation. The finer the grid division, the better. The finer the grid division, the more system resources will be occupied during the calculation process, and the longer the calculation time will be, but the accuracy of the calculation result will not be greatly improved. The denser the grid division, the better. It should be set in combination with the actual situation of the mechanical switch model. Therefore, in the simulation, combined with the actual situation of the mechanical switch model operation, the mesh division of the fluid domain is refined, and the boundary mesh division of the electrode is relatively fine.

[0068] Specifically, the criterion of the CTM in step 6 is:

[0069] The CTM model can be identified based on the relevant parameters obtained from the simulation results of the above MHD model.

[0070] Ion density N at the back-arc sheath boundary i It can be obtained by formula (12).

[0071]

[0072]

[0073]

[0074]

[0075]

[0076] Where l is the sheath length; ε 0 is the vacuum dielectric constant; e is the electron charge; Z is the average charge of the metal copper ion; u(t) is the voltage between the vacuum electrodes, which can be expressed by the transient recovery voltage TRV; U 0 is the sheath potential; Mi is the mass of the ion; v i is the ion movement speed; i(t) is the post-arc current after the sheath development begins; I 1 is the initial post-arc current value; l gap is the electrode spacing; is the diffusion decay time constant of the ions, δ AMP is the ion space distribution coefficient of the electrode gap. Ni is the plasma density, D is the effective arc diameter, N i0 is the initial plasma density behind the arc, and t1 is the initial time of sheath growth.

[0077] The decay of post-arc metal vapor is an important process for the insulation recovery of vacuum circuit breakers. After the arc is extinguished, there are still many neutral metal vapor particles between the gaps, which will gradually diffuse over time. The decay time of metal vapor is longer than the time for the post-arc sheath to be established, but it can be ignored compared to the arcing time. The metal vapor in the post-arc stage is ionized, which will increase the probability of reignition.

[0078] The metal vapor decays after zero crossing:

[0079]

[0080] in represents the attenuation coefficient of metal vapor density; S m represents the influence coefficient of contact ablation rate; ω is the angular frequency; K e The influence coefficient of the arc heating on the electrode causing the evaporation of the electrode material is taken into account; γ is the electrode corrosion rate, ranging from 30 to 110 μg / C; M is the atomic mass of the metal vapor, V = πR 2 l gap is the gap volume; k is the Boltzmann constant. R is the arc radius, N n (t) is the metal vapor density, S(t) is the contact ablation rate influence coefficient, Γ ev is the metal vapor flux density, dS is the microelement area of ​​the surface, and I is the current peak value.

[0081] According to the basic principle of gap breakdown, the reignition criteria can be: 1) electrical breakdown; 2) thermal breakdown; 3) when the sheath does not grow until it disappears, current appears between the electrodes again, resulting in breaking failure; 4) breakdown caused by metal vapor density greater than the critical value.

[0082] According to the judgment conditions of 1) and 2), the electric field strength E c and power P d The calculation method of is shown in equations (14) and (15). Electric field strength E c and power P d The critical values ​​of are difficult to obtain, and they vary with the actual working conditions of the vacuum interrupter. The specific values ​​can be determined based on experimental results.

[0083]

[0084]

[0085] According to the judgment condition in Article 3, the heavy breakdown criterion is given. Once the sheath boundary moves in the opposite direction, it is considered to penetrate the entire gap and reach the arc cathode, causing the breaking failure. Corresponding to the CTM model, the length of the sheath growth decreases with time until it reaches 0.

[0086] And l = 0 (16)

[0087] According to the reignition criteria in Article 4), TRV, neutral metal vapor density and gap sheath length jointly determine whether instantaneous restrike or delayed restrike occurs. Figure 5 As shown, n represents the neutral metal vapor density, d represents the sheath length, and n×d represents the positive limit of the product of the neutral metal vapor density and the gap sheath length.

[0088] According to the CTM model that takes into account the influence of the arc burning process, the product of the neutral metal vapor density and the gap sheath length can be calculated. Combined with the above-mentioned Baschen curve, the arc breaking limit can be determined.

[0089] Example:

[0090] The specific implementation steps of the simulation method of the fusion model of the arcing process and post-arcing process of a mechanical switch of the present invention are as follows:

[0091] Step 1: Figure 1 As shown, since the present invention assumes that the arc plasma is axisymmetric, a two-dimensional axisymmetric arc model is established based on the experimental model, 5 represents a carbon electrode with a pointed end, 6 represents a copper electrode, and 7 is a gas domain other than the electrode.

[0092] Step 2, Step 3, according to the above MHD model, five modules of flow field, thermal field, electric field, magnetic field and fluid particle tracking are selected for setting. The movement of the contact adopts dynamic grid operation, and the actual situation of arc plasma is combined to form a set of magnetohydrodynamic equations that conform to the characteristics of arc plasma.

[0093] like Figure 2 As shown, the boundary conditions constrained by the magnetohydrodynamic equations include a central axis 1, a first boundary 2 of the electrode, a second boundary 3 of the electrode, and a boundary 4 other than the central axis 1, the first boundary 2 of the electrode, and the second boundary 3 of the electrode; Figure 2 Also shown are a carbon electrode 5, a copper electrode 6, and a gas domain 7. The central axis 1 is on the left, the first boundary 2 of the electrode is above the carbon electrode 5, and the second boundary 3 of the electrode is below the copper electrode 6. The carbon electrode 5 is above, the copper electrode 6 is below, and the gas domain 7 is the internal area except the carbon electrode 5, the copper electrode 6, and the boundary 4 except the central axis 1, the first boundary 2 of the electrode, and the second boundary 3 of the electrode.

[0094] The flow state of the fluid is divided into two types: laminar flow and turbulent flow. When the fluid velocity is large enough, its flow state will change from laminar flow to turbulent flow. In this simulation, the arc is a free arc. It is assumed that the fluid is in a laminar state, and the airflow field is selected as a single-phase model in laminar flow. The entire air domain is affected by the volume force (Lorentz force).

[0095] In fluid heat transfer, because the electrode and air are two types of substances, and the heat transfer modes of the two types of substances are different, the two parts are set separately in the simulation, and the carbon electrode 5 and the copper electrode 6 are set as solids, and the air is a fluid, and they are processed using different formulas. In the boundary settings, thermal insulation is set, that is, -n·q=0, where q is the conductive heat flux and n is the unit area. At the same time, the initial temperature of the electrode and air domain is set to room temperature.

[0096] Both the electric field and the magnetic field belong to the AC / DC module. In the electric field, the entire calculation area follows the law of conservation of current. Set electrical insulation, that is, -n·J=0 (J is the current density). Set grounding (V=0), and set the normal current density at the first boundary 2 of the electrode to couple with the circuit. In the magnetic field, except for the central axis 1, all boundaries including the boundaries of the two electrodes are set to magnetic insulation.

[0097] Electrodes are divided into cathodes and anodes, so the temperature coupling between plasma and electrode interface is divided into two categories, one is the temperature coupling between anode and electrode interface, and the other is the temperature coupling between cathode and electrode interface. Arc plasma includes two kinds of particles, positively charged ions and negatively charged electrons. When a suitable voltage is applied to both ends of the electrode, the cathode will emit electrons to the anode. While emitting electrons, the positive ions in the plasma move toward the cathode at a certain acceleration, which will increase the electrode temperature. As the temperature rises, the hot cathode will emit more electrons, which is also the reason for cathode cooling. This simulation uses the mechanism of cathode thermal emission. Therefore, in the temperature coupling between plasma and electrode boundary, the formula used for the cathode is:

[0098]

[0099]

[0100] J ion =|J·n|-J elec (19)

[0101] The left side of equation (17) is the heat flux, the first term on the right side is the heat flux generated by electrons, and the second term is the heat flux generated by ions, J elec is the electron current density, φ is the electrode surface work function, J ion is the ion current density, V ion is the ionization potential, is the temperature gradient. Equation (18) is the calculation formula for the electron current density, which is the calculation formula for the cathode saturated emission current density, where A R is the effective Richardson constant, q is the electron charge, φ eff is the electrode surface work function, k Bis the Boltzmann function. Equation (19) is the calculation formula for ion current density, where |J·n| is the interface normal current density.

[0102] Set up the Fluid Particle Tracing module, add material properties to each fluid flow particle tracing model, and add the relative dielectric constant and conductivity of the particles including the dielectrophoretic force field condition.

[0103] Dynamic mesh setting: When the mechanical switch is breaking the circuit, the static contact is fixed and the moving contact is open. Specifically, in the simulation implementation, the moving mesh technology is selected to make the simplified moving contact move with the solution time. The movement of the moving contact will inevitably affect the quality of the surrounding mesh. When the mesh is stretched and deformed to a certain limit, the calculation result will be wrong and the calculation cannot be completed. This requires the mesh to be updated according to the real-time mesh quality during the simulation calculation, that is, the automatic re-division of the mesh. When the local mesh is stretched and deformed with the movement of the contact, and the mesh quality coefficient of the last time step before the solver stops is lower than the preset threshold, the solution process is paused and a set of meshes is re-divided according to the initial mesh parameter settings for that moment. After the mesh adaptation is completed, the solution calculation continues until the next mesh re-division. After several re-division processes, the calculation of the entire time domain is completed. Different from the previous dynamic mesh with specified mesh speed, due to the use of the specified mesh displacement option, the material coordinates of the moving contact must be displaced together with the geometric coordinates to meet the calculation requirements of the contact circumferential breaking. This requires that the simulation calculation must link the material coordinate system and the geometric coordinate system together through mathematical expressions and make them move simultaneously.

[0104] Step 4: Perform the necessary meshing operations in the finite element software on the MHD model established in the above steps:

[0105] There are generally two modes of mesh division. One is the software default, which is controlled by the physical field; the other is user-defined, and the unit shape and unit size can be set. In the calculation of finite element software, mesh division is also a very important content. The number, quality, refinement and density distribution of the mesh all have a crucial impact on the convergence of the solved equations. Any flaws in the mesh will affect the calculation process and cause the results to not converge, thus failing to complete the simulation calculation. The finer the mesh division, the better. The finer the mesh division, the more system resources will be occupied during the calculation process, and the longer the calculation time will be, but the accuracy of the calculation results will not be greatly improved. From this perspective, the denser the mesh division, the better. It should be set in combination with the actual situation of the model. Therefore, in the simulation, combined with the actual situation of the model calculation, the gas domain mesh division is refined (the unit size range is: 0.025-0.875cm), and the electrode boundary mesh division is relatively refined (the unit size range is: 0.01-0.7cm). Figure 3 shown.

[0106] Step 5: Perform model calculation to obtain various transient characteristic indicators during the mechanical switch opening process, such as Figure 4a , Figure 4b , Figure 4c , Figure 4d , Figure 4e , Figure 4f shown.

[0107] Step 6: Use the results of the MHD simulation as input parameters of the CTM to determine the breaking capacity of the mechanical switch and the breaking limit, so as to determine the breaking capacity of the mechanical switch under different breaking current frequencies.

[0108] The above embodiments are only for illustrating the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A simulation method for the fusion model of arcing process and post-arcing process of mechanical switches. It is characterized in that The steps include: Step 1, establish a two-dimensional axisymmetric mechanical switch model; Step 2: In order to facilitate the convergence of simulation calculations and reduce the complexity of simulation, several assumptions are introduced during the simulation process to constrain the mechanical switch model; Step 3, combining the actual situation of arc plasma to form a set of magnetohydrodynamic equations that conform to the characteristics of arc plasma; Step 4, boundary condition setting: select the flow field, thermal field, electric field, magnetic field and fluid particle tracking modules according to the magnetic fluid dynamic model, and select the dynamic grid module for simulation of the opening and closing action of the mechanical switch simulation model; Step 5, combining the actual situation of the mechanical switch model operation, perform user-defined grid division; Step 6, based on the particle motion simulation results obtained by the magnetic fluid dynamic model, the continuous transition model is used in combination with the influence of the arcing process to calculate the parameters of the sheath growth process, obtain the influence of frequency on the post-arc sheath growth process, and determine the breaking capacity of the mechanical switch.

2. According to claim 1, a mechanical switch arcing process and post-arc process fusion model simulation method, It is characterized in that The constraints in step 2 are: (1) Assume that the arc plasma to be solved is an equilibrium plasma, that is, it satisfies the local thermodynamic equilibrium state; (2) Assuming that the arc plasma is axisymmetric, the flow of the arc plasma generated by the electromagnetic force is laminar; (3) The density, electrical conductivity, thermal conductivity, constant-pressure heat capacity, and dynamic viscosity coefficient of arc plasma are only functions of temperature.

3. According to the method for simulating the arcing process and post-arcing process fusion model of a mechanical switch according to claim 1, It is characterized in that The magnetohydrodynamic equations in step 3 include: mass conservation equation, radial momentum conservation equation, axial momentum conservation equation, energy conservation equation, current continuity equation, Maxwell's equations, and Ohm's law.

4. According to claim 1, a mechanical switch arcing process and post-arcing process fusion model simulation method, It is characterized in that The boundary conditions in step 4 are set as: The magnetofluid dynamic model selects the flow field, thermal field, electric field, magnetic field and fluid particle tracking modules for setting, and the movement of the contact adopts the dynamic mesh operation; the objects that need to be set include the dynamic and static electrodes, fluid domain, central axis and moving mesh.

5. The method for simulating the arcing process and post-arcing process fusion model of a mechanical switch according to claim 1, It is characterized in that The user-defined grid division in step 5 includes dividing the grid of the fluid domain into a refined grid, where the refined grid is defined as: the grid size parameter range is 0.025-0.875 mm; dividing the boundary grid of the electrode into a finer grid, where the finer grid is defined as the grid size parameter range is 0.01-0.7 mm.

6. The method for simulating the arcing process and post-arcing process fusion model of a mechanical switch according to claim 1, It is characterized in that The criterion of the continuous transition model in step 6 is: comparing the product of the neutral metal vapor particle and the sheath length with the Paschen curve to determine the breaking capacity of the mechanical switch.

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