Finite element-based electric energy metering box temperature field simulation analysis method

Abstract

The invention provides an electric energy metering box temperature field simulation analysis method based on finite elements, and relates to the technical field of electrical equipment fault diagnosis. The method comprises the following steps: constructing a three-dimensional structure model considering asymmetric layout and material attributes of internal elements; identifying key heating elements and establishing a dynamic heat source; constructing an unsteady state heat conduction model by combining a Fourier law and an energy conservation equation; setting environment related boundary conditions; and outputting a temperature distribution diagram and an abnormal hot spot early warning result, thereby realizing accurate modeling and risk pre-judgment of the thermal behavior of the electric energy metering box.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical equipment fault diagnosis, and in particular to a finite element-based temperature field simulation analysis method for an electric energy metering box. Background Art

[0002] With the development of smart grids and distributed energy, low-voltage energy meter boxes are playing an increasingly critical role in user access, energy consumption measurement, and load monitoring. Modern energy meter boxes often integrate multiple circuit devices, energy meters, and communication modules, resulting in increasingly compact structures and increasingly complex operating environments.

[0003] To meet the high-precision and high-reliability requirements of electricity metering, meter box design tends to be multi-circuit integrated, high-density layout, and intelligent heat dissipation control. The application of the finite element method (FEM) in complex thermal coupling modeling has become a research hotspot, and more and more researchers are trying to shift from static thermal design to dynamic thermal behavior simulation.

[0004] Most existing technologies rely on steady-state thermal field models of medium and high voltage equipment, and lack modeling methods for the non-steady-state, multi-harmonic, and multi-heat source dynamic characteristics of low-voltage electricity metering boxes; they are unable to accurately simulate the multi-physical field coupling characteristics of resistive heating, electromagnetic eddy currents, contact thermal resistance, and radiation environment; and their early warning capabilities for potential overheating risks of devices are insufficient, which cannot meet the needs of operation, maintenance, and abnormality diagnosis. Summary of the Invention

[0005] In order to overcome the shortcomings of the existing technology, the purpose of the present invention is to provide a finite element-based temperature field simulation and analysis method for an electric energy meter box, which can simulate the dynamic temperature distribution inside the electric energy meter box with high precision and realize effective early warning of abnormal hot spots, thereby improving thermal safety design and operational reliability.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A finite element-based temperature field simulation analysis method for an electric energy meter box includes:

[0008] Constructing a three-dimensional structural model of an electric energy meter box; the structural model is based on the asymmetric spatial layout of internal components of the electric energy meter box and composite material thermal parameter modeling; the internal components include an electric energy meter, a circuit breaker, a copper busbar connector, and an insulating support frame;

[0009] Identifying key heating elements among the internal elements as heat source calculation objects, and calculating resistance losses based on structural parameters, current load data, and harmonic distortion rate of the key heating elements to form a dynamic heating power data set;

[0010] The dynamic heat generation power distribution is used as a non-uniform heat source input, and a three-dimensional non-steady-state heat conduction differential equation inside the electric energy meter box is established in combination with Fourier's law and the energy conservation equation;

[0011] Taking the three-dimensional unsteady-state heat conduction differential equation and the dynamic heating power data set as input, a finite element numerical calculation model for temperature simulation is constructed;

[0012] Setting simulation boundary conditions according to the operating environment of the electric energy meter box;

[0013] Based on the finite element numerical calculation model and the simulation boundary conditions, a regional grid division strategy and an adaptive time step algorithm are adopted to perform temperature field transient simulation, and output a temperature field distribution map and abnormal hot spot warning results inside the electric energy meter box.

[0014] Preferably, the key heating elements include an electric energy meter chip, a circuit breaker contact and a copper busbar connection node.

[0015] Preferably, constructing a three-dimensional structural model of the electric energy meter box includes:

[0016] Extracting the geometric dimensions and structural configuration of the housing of the electric energy meter box and determining the properties of the double-layer material used for the housing; the double-layer material properties include the thermal conductivity, thickness, and cavity spacing of the inner aluminum alloy layer and the outer polycarbonate layer;

[0017] Obtaining the three-dimensional coordinates and installation parameters of the internal components based on the design drawings; the installation parameters include the installation position, connection relationship and spatial arrangement of the electric energy meter, circuit breaker, copper busbar connector and insulation support frame;

[0018] Establishing a geometric model of each of the internal components in a three-dimensional modeling software, and setting thermophysical parameters according to the material of each of the internal components; the thermophysical parameters include thermal conductivity, density and specific heat capacity;

[0019] The geometric models are assembled to generate an initial structural model of an electric energy metering box with an asymmetric spatial layout, and the initial structural model is imported into a finite element simulation platform for model verification and mesh division preprocessing to obtain the three-dimensional structural model.

[0020] Preferably, key heating elements among the internal elements are identified as heat source calculation objects, and resistance losses are calculated based on the structural parameters, current load data, and harmonic distortion rate of the key heating elements to form a dynamic heating power data set, including:

[0021] Perform real-time current sampling on the electric energy meter chip, the circuit breaker contacts and the copper busbar connector to obtain the fundamental wave effective value I1 and the effective value of each order harmonic I h ;

[0022] Extracting the wire length L and cross-sectional area A of each key heating element as input of the structural parameters;

[0023] According to the real-time temperature T, the resistivity is calculated using the temperature-dependent resistivity function; the expression of the temperature-dependent resistivity function ρ(T) is: ρ(T) = ρ 20 [1+γ·(T-20)]; where ρ 20 is the base resistivity of the conductor at 20°C, γ is the temperature coefficient of resistance; T is the temperature field variable;

[0024] The weighted coefficient of the harmonic correction factor is calculated according to the frequency weight formula; the frequency weight formula is: Among them, w h is the frequency weight coefficient corresponding to the h-th order harmonic, α is the frequency attenuation factor, ranging from 0.5 to 1.5, n is the highest order considered in the harmonic analysis, and k is the harmonic order variable that participates in the accumulation in the weight normalization calculation;

[0025] And according to the formula Calculate the harmonic correction factor; where κ is the harmonic correction factor;

[0026] Based on the formula Calculate the resistance loss power density q; where A is the cross-sectional area of ​​the conductor;

[0027] The resistance loss power density q is mapped to the node area corresponding to the key heating components in the three-dimensional structural model to form a dynamic heating power data set that changes with time.

[0028] Preferably, the dynamic heating power distribution is used as a non-uniform heat source input, and combined with Fourier's law and the energy conservation equation, a three-dimensional unsteady-state heat conduction differential equation inside the electric energy meter box is established, including:

[0029] Mapping the dynamic heating power data set into a non-uniform internal heat source term Q(x, y, z, t) and embedding it into the corresponding node in the three-dimensional structural model; where x, y, and z are the x-axis coordinates, y-axis coordinates, and z-axis coordinates of the three-dimensional spatial position, respectively, and t is time;

[0030] According to Fourier's law expression Construct a local relationship between heat flux and temperature gradient; where λ(T) is the temperature-dependent thermal conductivity, is the heat flux vector, is the temperature gradient;

[0031] According to the energy conservation equation, the non-uniform internal heat source term Q(x, y, z, t) and the local relationship are combined to establish the unsteady three-dimensional heat conduction differential equation: Where ρ is the material density, c p is the material's specific heat capacity at constant pressure, and T is the temperature field variable;

[0032] Set the material area attributes and assign different thermal physical parameters to different component areas; the thermal physical parameters include ρ, c p , λ(T) to realize temperature field modeling under heterogeneous material conditions.

[0033] Preferably, the three-dimensional unsteady-state heat conduction differential equation and the dynamic heating power data set are used as input to construct a finite element numerical calculation model for temperature simulation, including:

[0034] The corresponding thermal conductivity forms are assigned to different material areas in the electric energy meter box structure model, among which the temperature-dependent thermal conductivity scalar λ is set for the isotropic material area. s (T), sets the temperature-dependent thermal conductivity tensor Λ(T) for the anisotropic material region;

[0035] Introduce the electromagnetic induction heat source term Q in the conductive component area em (x, y, z, t), the electromagnetic induction heat source term Q em (x,y,z,t) including the eddy current loss term Q eddy and the hysteresis loss term Q hyst , the formula is: Q em (x,y,z,t)=Q eddy +Q hyst ; Where σ is the conductivity, ω is the current angular frequency, B is the effective value of the magnetic induction intensity, d is the conductor thickness, k h is the hysteresis coefficient, f is the frequency, B m is the maximum magnetic induction intensity, n is the hysteresis index;

[0036] An interface thermal resistance model is set at the copper busbar connection node and the circuit breaker contact; the interface thermal resistance model R c The calculation formula is: Where δ is the thickness of the interface gap, λ int is the thermal conductivity of the interface material, R int is the contact thermal resistance constant;

[0037] The electromagnetic induction heat source term Q em (x, y, z, t) and the interface thermal resistance model are substituted into the three-dimensional unsteady-state heat conduction differential equation to construct a finite element simulation calculation model; the formula of the finite element simulation calculation model is: Among them, Q c(x,y,z,t) is due to R c The equivalent volume heat source term formed by the local temperature difference near the interface caused by Where ΔT is the temperature difference on both sides of the contact interface, A′ is the area of ​​the thermal contact interface, and V is the local unit volume involved in heat transfer.

[0038] Preferably, setting simulation boundary conditions according to the operating environment of the electric energy meter box includes:

[0039] According to Newton's cooling law, a convection heat transfer Robin boundary condition is applied to the outer surface of the electric energy meter box; the boundary heat flux density of the convection heat transfer Robin boundary condition is defined as q conv (t) = h(t)[T surf (t)-T env (t)]; T surf (t) is the instantaneous temperature of the shell surface, where the heat transfer coefficient h(t) is determined according to the following criteria:

[0040] When the ambient temperature T env ≤35℃ and temperature gradient When the natural convection coefficient h nat =5~10W / (m 2 K);

[0041] When T env >35℃ and When the forced convection coefficient h forced =20~50W / (m 2 K);

[0042] If the relative humidity inside the metering box RH(t) ≥ 60%, use the formula Corrected natural convection coefficient and forced convection coefficient; where h0 is the base heat transfer coefficient, take h nat or h forced The current value of , β is the humidity sensitivity coefficient;

[0043] When the electric energy meter box is in an outdoor solar radiation environment, a composite radiation boundary condition is applied based on plane radiation and the Stefan-Boltzmann law. The heat flux density per unit area under the composite radiation boundary condition is calculated as follows: Among them, q rad (t) is the radiation heat flux density per unit area, η is the solar radiation absorption rate, G solar (t) is the solar irradiance, ∈ is the surface emissivity, and σ' is the Stefan-Boltzmann constant, which is 5.67×10 -8 ;T sky (t) is the equivalent radiation temperature of the sky;

[0044] qconv (t) and q rad (t) A Neumann-type or Robin-type heat flux boundary is loaded onto the outer surface of the finite element numerical calculation model and used as the boundary input for solving the temperature field.

[0045] Preferably, based on the finite element numerical calculation model and the simulation boundary conditions, a regional grid division strategy and an adaptive time step algorithm are adopted to perform a temperature field transient simulation, and output a temperature field distribution diagram and abnormal hot spot warning results inside the electric energy meter box, including:

[0046] A tetrahedron encrypted grid is used in the area of ​​the key heating element; the grid characteristic size h of the tetrahedron encrypted grid is fine ≤0.5mm;

[0047] A hexahedral sparse and dense grid is used in the housing and insulating support frame area of ​​the electric energy meter box; the grid characteristic size h of the hexahedral sparse and dense grid is coarse ≥2mm;

[0048] The initial time step Δt0 is set and it is iteratively updated according to the adaptive time step algorithm; the expression of the adaptive time step algorithm is: Among them, ε T is the temperature variation tolerance, Δt max is the maximum allowed time step, Δt n+1 is the time step between step n and step n+1, T i is the instantaneous temperature of node i at the current time step,

[0049] Solve the discretized unsteady heat conduction equations in each time step; the discretized unsteady heat conduction equations are And the energy residual convergence criterion is adopted Determine the iterative convergence; where C is the heat capacity matrix, K(T) is the temperature-dependent thermal conductivity matrix, and Q n+1 is the comprehensive heat source load vector at time step n+1, R E is the energy residual, ε E is the energy residual tolerance, T n is the temperature vector of all discrete nodes at the nth time step, and t is the time;

[0050] After the simulation is completed, the result field is post-processed to generate the temperature field distribution diagram T(x, y, z, t end ), and calculate the temperature extremes of all nodes. If T i ≥T limit or The corresponding unit is marked as an abnormal hotspot and the abnormal hotspot warning result is output; wherein, Tlimit is the upper limit of component safety temperature, γ crit is the preset temperature rise rate warning threshold, t end is the endpoint timestamp of the entire time advancement process, x, y, and z are the x-axis coordinate, y-axis coordinate, and z-axis coordinate of the three-dimensional space position respectively;

[0051] The temperature field distribution map and the abnormal hot spot warning results are used as simulation outputs for subsequent operation and maintenance decision-making.

[0052] The present invention discloses the following technical effects:

[0053] The present invention achieves high-fidelity restoration of the real structure and thermal physical properties of the electric energy meter box by constructing a three-dimensional structural model that takes into account the asymmetric spatial layout of internal components and the thermal parameters of composite materials; by identifying key heating components and calculating the resistance loss based on structural parameters, current load and harmonic distortion rate, a dynamic heating power data set is formed, thereby improving the accuracy and timeliness of heat source modeling; combining Fourier's law and the energy conservation equation to establish a non-steady-state heat conduction differential equation, and constructing a finite element numerical calculation model of multi-physical field coupling, so that the simulation process can reflect complex spatial heat conduction behavior; by setting simulation boundary conditions that meet the operating environment and introducing a regional grid division strategy and an adaptive time step algorithm, the numerical stability and efficiency of the temperature field simulation are further improved; finally, the internal temperature field distribution map of the electric energy meter box and the abnormal hotspot warning results are output, which helps to detect local overheating risks in advance and provides an accurate and reliable basis for product design optimization and operation safety assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only 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.

[0055] Figure 1 A flow chart of a method provided by an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of an electric energy metering box provided in an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of internal heat dissipation of an electric energy meter box provided in an embodiment of the present invention;

[0058] Figure 4 This is a schematic diagram of an electric energy meter box in a three-dimensional rectangular coordinate system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] The purpose of the present invention is to provide a finite element-based temperature field simulation analysis method for an electric energy meter box, which can simulate the dynamic temperature distribution inside the electric energy meter box with high precision and realize effective early warning of abnormal hot spots, thereby improving thermal safety design and operational reliability.

[0061] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0062] Figure 1 A flow chart of the method provided in the embodiment of the present invention is shown in FIG. Figure 1 As shown, the present invention provides a finite element-based temperature field simulation analysis method for an electric energy meter box, comprising:

[0063] Step 100: Construct a three-dimensional structural model of the energy meter box. The structural model is based on the asymmetric spatial layout of the internal components of the energy meter box and the thermal parameters of the composite material. The internal components include the energy meter, circuit breaker, copper busbar connector, and insulation support frame.

[0064] Step 200: Identify key heating elements among the internal components as heat source calculation objects, and calculate resistance losses based on the structural parameters, current load data, and harmonic distortion rate of the key heating elements to form a dynamic heating power data set;

[0065] Step 300: Using the dynamic heat generation power distribution as a non-uniform heat source input, and combining Fourier's law and the energy conservation equation, a three-dimensional unsteady-state heat conduction differential equation inside the electric energy meter box is established;

[0066] Step 400: using the three-dimensional unsteady-state heat conduction differential equation and the dynamic heating power data set as input to construct a finite element numerical calculation model for temperature simulation;

[0067] Step 500: setting simulation boundary conditions according to the operating environment of the electric energy meter box;

[0068] Step 600: Based on the finite element numerical calculation model and simulation boundary conditions, a regional grid division strategy and an adaptive time step algorithm are adopted to perform a temperature field transient simulation, and output a temperature field distribution diagram inside the electric energy meter box and abnormal hot spot warning results.

[0069] Preferably, the key heating elements include an electric energy meter chip, a circuit breaker contact and a copper busbar connection node.

[0070] Preferably, constructing a three-dimensional structural model of the electric energy meter box includes:

[0071] Extracting the geometric dimensions and structural configuration of the housing of the electric energy meter box and determining the properties of the double-layer material used for the housing; the double-layer material properties include the thermal conductivity, thickness, and cavity spacing of the inner aluminum alloy layer and the outer polycarbonate layer;

[0072] Obtaining the three-dimensional coordinates and installation parameters of the internal components based on the design drawings; the installation parameters include the installation position, connection relationship and spatial arrangement of the electric energy meter, circuit breaker, copper busbar connector and insulation support frame;

[0073] Establishing a geometric model of each of the internal components in a three-dimensional modeling software, and setting thermophysical parameters according to the material of each of the internal components; the thermophysical parameters include thermal conductivity, density and specific heat capacity;

[0074] The geometric models are assembled to generate an initial structural model of an electric energy metering box with an asymmetric spatial layout, and the initial structural model is imported into a finite element simulation platform for model verification and mesh division preprocessing to obtain the three-dimensional structural model.

[0075] like Figures 2 to 4 As shown, in this embodiment, constructing a three-dimensional structural model of the electric energy meter box includes extracting the structural parameters of the outer shell and internal components and restoring the space. First, the geometric dimensions and structural configuration information of the outer shell of the electric energy meter box are extracted, including the overall length, width, height of the outer shell and the panel opening characteristics, and the double-layer material structure used is determined: the inner layer is made of aluminum alloy with a thermal conductivity of approximately 205W / (m·K) and a thickness of 1.5mm; the outer layer is made of polycarbonate material with a thermal conductivity of approximately 0.22W / (m·K) and a thickness of 2mm; a 5mm air insulation cavity is set between the two layers to suppress the conduction influence of the external thermal environment. The above structural parameters are obtained by combining physical measurements with product drawings, and serve as the basic input for subsequent structural modeling.

[0076] Subsequently, the spatial layout information of the internal components of the electricity meter box is obtained based on the two-dimensional design drawings and structural BOM (bill of materials), including the position coordinates, installation direction and connection relationship of the electricity meter, circuit breaker, copper busbar connector and insulation support frame. This information is imported into 3D modeling software (such as SolidWorks or Creo) for fine modeling. A complete geometric model is established for each component, and its thermal physical parameters are set according to the actual material: for example, the electricity meter chip uses epoxy encapsulated silicon material with a density of 1200kg / m 3, the specific heat capacity is 850J / (kg·K), the thermal conductivity is 0.2W / (m·K); the copper busbar is made of industrial pure copper with a density of 8960kg / m 3 , specific heat capacity is 385 J / (kg·K), and thermal conductivity is 390 W / (m·K). All component parameters are derived from actual sample tests or manufacturer's technical manuals to ensure the engineering feasibility of simulation modeling.

[0077] After completing the modeling of all internal components, the component models are assembled into a unified coordinate system to generate an initial structural model with an asymmetric spatial layout, which fully reflects the geometric relationship between the functional components under real working conditions. The model is then imported into a finite element simulation platform (such as ANSYS Workbench) for meshing pre-processing. In key heating areas (such as electricity meter chips, circuit breaker contacts, and copper busbar connection nodes), tetrahedral encryption meshes are used, and the unit size is controlled within 0.5mm; in areas with small temperature gradients (such as shells and support frames), sparse and dense transition meshes are used to ensure a balance between simulation accuracy and computational efficiency. After completing the meshing, geometric consistency checks and physical property parameter reviews are performed, and finally a three-dimensional structural model that can be used for thermal field simulation is obtained.

[0078] Preferably, key heating elements among the internal elements are identified as heat source calculation objects, and resistance losses are calculated based on the structural parameters, current load data, and harmonic distortion rate of the key heating elements to form a dynamic heating power data set, including:

[0079] Perform real-time current sampling on the electric energy meter chip, the circuit breaker contacts and the copper busbar connector to obtain the fundamental wave effective value I1 and the effective value of each order harmonic I h ;

[0080] Extracting the wire length L and cross-sectional area A of each key heating element as input of the structural parameters;

[0081] According to the real-time temperature T, the resistivity is calculated using the temperature-dependent resistivity function; the expression of the temperature-dependent resistivity function ρ(T) is: ρ(T) = ρ 20 [1+γ·(T-20)]; where ρ 20 is the base resistivity of the conductor at 20°C, γ is the temperature coefficient of resistance; T is the temperature field variable;

[0082] The weighted coefficient of the harmonic correction factor is calculated according to the frequency weight formula; the frequency weight formula is: Among them, w h is the frequency weight coefficient corresponding to the h-th order harmonic, α is the frequency attenuation factor, ranging from 0.5 to 1.5, n is the highest order considered in the harmonic analysis, and k is the harmonic order variable that participates in the accumulation in the weight normalization calculation;

[0083] And according to the formula Calculate the harmonic correction factor; where κ is the harmonic correction factor;

[0084] Based on the formula Calculate the resistance loss power density q; where A is the cross-sectional area of ​​the conductor;

[0085] The resistance loss power density q is mapped to the node area corresponding to the key heating components in the three-dimensional structural model to form a dynamic heating power data set that changes with time.

[0086] In this implementation, to identify and quantify the heat source intensity of key heat-generating components within the energy meter box, the energy meter chip, circuit breaker contacts, and copper busbar connectors were first selected as the primary heat sources. High-frequency current sensors sampled the currents of these components in real time during operation, and frequency domain analysis was used to extract the fundamental current and multiple harmonic currents. Simultaneously, geometric information about these components, including the length and cross-sectional area of ​​the conductors, was extracted from the three-dimensional structural model for subsequent loss analysis. This basic data constituted the structural and electrical input parameters required for heat generation modeling.

[0087] After obtaining the temperature of key components under different working conditions, the trend of changes in their conductive properties at the current temperature is determined based on the thermal sensitivity of the material. Specifically, the resistance characteristics of each component at the current temperature are calculated through the preset temperature-resistivity relationship. At the same time, in order to consider the additional energy consumption caused by high-frequency harmonics in the current, frequency-related weighting coefficients are assigned to harmonic current components of different orders. The size of the weighting coefficient is set according to the harmonic order. The higher the frequency of the harmonic, the more significant its impact on the loss. All harmonic currents are corrected and superimposed through these weights to form a comprehensive harmonic correction factor to reflect the actual energy consumption level under complex loads.

[0088] Combining the above electrical parameters, structural parameters and temperature data, the resistive heating power generated by each key heating element per unit volume is calculated. This power value not only reflects the basic loss caused by the main current flux, but also covers the additional loss caused by harmonics and the dynamic influence of temperature on resistance. Subsequently, these heating powers are mapped to the corresponding component node areas in the three-dimensional structural model according to their spatial positions to construct a dynamic heating power data set with time-series variation characteristics. This data set is used as a non-uniform heat source input for subsequent temperature field simulation, making the model more consistent with the evolution of thermal behavior under real working conditions.

[0089] Preferably, the dynamic heating power distribution is used as a non-uniform heat source input, and combined with Fourier's law and the energy conservation equation, a three-dimensional unsteady-state heat conduction differential equation inside the electric energy meter box is established, including:

[0090] Mapping the dynamic heating power data set into a non-uniform internal heat source term Q(x, y, z, t) and embedding it into the corresponding node in the three-dimensional structural model; where x, y, and z are the x-axis coordinates, y-axis coordinates, and z-axis coordinates of the three-dimensional spatial position, respectively, and t is time;

[0091] According to Fourier's law expression Construct a local relationship between heat flux and temperature gradient; where λ(T) is the temperature-dependent thermal conductivity, is the heat flux vector, is the temperature gradient;

[0092] According to the energy conservation equation, the non-uniform internal heat source term Q(x, y, z, t) and the local relationship are combined to establish the unsteady three-dimensional heat conduction differential equation: Where ρ is the material density, c p is the material's specific heat capacity at constant pressure, and T is the temperature field variable;

[0093] Set the material area attributes and assign different thermal physical parameters to different component areas; the thermal physical parameters include ρ, c p , λ(T) to realize temperature field modeling under heterogeneous material conditions.

[0094] In this embodiment, the previously generated dynamic heating power dataset is first used as a heat source input and mapped to the spatial locations corresponding to the key heating components in the three-dimensional structural model. During the mapping process, the corresponding grid cells of the energy meter chip, circuit breaker contacts, and copper busbar connection nodes are identified one by one in the finite element simulation software based on their physical geometric locations. The corresponding thermal power density values ​​are then loaded onto these unit nodes, forming a non-uniform internal heat source distribution that varies with position in three-dimensional space and has dynamic characteristics over time. This heat source distribution serves as a driving factor in subsequent heat conduction calculations, directly affecting the temperature evolution process within the model.

[0095] Subsequently, based on the physical laws of heat conduction, a mathematical description model of heat transfer inside the material is established. Specifically, based on Fourier's law of heat conduction, the system links the heat flux density inside each computing unit with the temperature difference between its surrounding nodes, thereby determining the direction and rate of local heat transfer. At the same time, based on the principle of conservation of energy, the system constructs the energy balance relationship of each computing unit per unit time, that is, the heat generated per unit volume, the sum of the imported and exported heat fluxes, and the heat energy absorbed by its own temperature change must be conserved. The above two physical laws form a set of partial differential equations that describe the changes of temperature field with time and space at the numerical level, which serves as the core calculation framework of the simulation model.

[0096] In order to ensure that the constructed heat conduction model can reflect the actual thermal behavior of various components inside the electricity meter box, unique thermophysical parameters are set for each material area in the model. These parameters mainly include the density, specific heat capacity at constant pressure and thermal conductivity of the material, which can be obtained through material sample testing, product manuals or standard data manuals. For example, the density of the copper busbar is about 8900 kilograms per cubic meter, the specific heat capacity is about 385 joules per kilogram per degree Celsius, and the thermal conductivity coefficient can be set to 390 watts per meter per Kelvin; the polycarbonate shell material has lower thermal conductivity and larger heat capacity. For materials with anisotropic thermal conductivity properties (such as pressed copper busbars or laminated composite panels), the system supports setting thermal conductivity values ​​in different directions. By setting differentiated parameters for different component areas, refined temperature field modeling under heterogeneous material conditions is achieved.

[0097] Preferably, the three-dimensional unsteady-state heat conduction differential equation and the dynamic heating power data set are used as input to construct a finite element numerical calculation model for temperature simulation, including:

[0098] The corresponding thermal conductivity forms are assigned to different material areas in the electric energy meter box structure model, among which the temperature-dependent thermal conductivity scalar λ is set for the isotropic material area. s (T), sets the temperature-dependent thermal conductivity tensor Λ(T) for the anisotropic material region;

[0099] Introduce the electromagnetic induction heat source term Q in the conductive component area em (x, y, z, t), the electromagnetic induction heat source term Q em (x,y,z,t) including the eddy current loss term Q eddy and the hysteresis loss term Q hyst , the formula is: Q em (x,y,z,t)=Q eddy +Q hyst ; Where σ is the conductivity, ω is the current angular frequency, B is the effective value of the magnetic induction intensity, d is the conductor thickness, k h is the hysteresis coefficient, f is the frequency, B m is the maximum magnetic induction intensity, n is the hysteresis index;

[0100] An interface thermal resistance model is set at the copper busbar connection node and the circuit breaker contact; the interface thermal resistance model R c The calculation formula is: Where δ is the thickness of the interface gap, λ int is the thermal conductivity of the interface material, R int is the contact thermal resistance constant;

[0101] The electromagnetic induction heat source term Q em(x, y, z, t) and the interface thermal resistance model are substituted into the three-dimensional unsteady-state heat conduction differential equation to construct a finite element simulation calculation model; the formula of the finite element simulation calculation model is: Among them, Q c (x,y,z,t) is due to R c The equivalent volume heat source term formed by the local temperature difference near the interface caused by c Where ΔT is the temperature difference on both sides of the contact interface, A′ is the area of ​​the thermal contact interface, and V is the local unit volume involved in heat transfer.

[0102] In this embodiment, in order to realize the dynamic modeling of the temperature change process inside the electric energy meter box, the aforementioned generated dynamic heating power data set is first embedded into the three-dimensional structural model. The specific approach is: according to the spatial position of each key heating element, the corresponding thermal power density value is mapped to the grid node area where it is located, so that it forms a non-uniform heat source term that changes with time and space distribution in the entire structural model. Subsequently, based on the physical principles of heat transfer, the classical heat conduction law is used to establish the local relationship between heat flux density and temperature distribution, and at the same time, this local relationship is combined with the principle of conservation of energy to form a non-steady-state heat conduction model that describes the three-dimensional temperature change with time. In this model, the thermophysical properties of different materials need to be set separately, including density, specific heat capacity and thermal conductivity, to ensure that the model can truly reflect the heterogeneous thermal response behavior of different components in the electric energy meter box.

[0103] After establishing a complete three-dimensional heat conduction model, in order to achieve its numerical solution, it needs to be converted into a simulation calculation model suitable for finite element solution. First, in the three-dimensional structure, different forms of thermal conductivity expression are set for different material areas: for components with uniform heat conduction characteristics, such as shells and brackets, scalar thermal conductivity coefficients are used; for components with different heat conduction directions, such as copper busbars, tensor-based thermal conductivity parameters are used. Secondly, electromagnetic induction heating terms are introduced in the conductive component area to consider two types of additional heat sources generated under AC excitation: one is the eddy current effect caused by magnetic field changes inside the conductor, and the other is the internal energy loss caused by the hysteresis characteristics of the material. The input parameters required for the above two heat sources, including the material's electrical conductivity, magnetic field strength, excitation frequency, magnetic permeability and component geometric characteristics, can all be obtained through sample testing, electrical design parameters or simulation tools, and have clear engineering sources.

[0104] To further improve the accuracy of temperature simulation, an interface thermal resistance model is introduced at the connections between conductors inside the energy meter box (such as copper busbar overlap locations and circuit breaker contacts). This model takes into account the adverse effects of tiny air gaps, contact roughness, and interface fillers present in the actual assembly process on heat conduction. The specific method is as follows: based on the interface thickness, the thermal conductivity of the interface material, and the contact thermal resistance constant obtained from existing literature or experiments, the heat flux impedance at this location is calculated; and this is equivalently converted into a local volume heat source term to correct the heat flow changes at nodes near the interface. Finally, the dynamic heat source, electromagnetic additional heat source, and interface thermal resistance effect are loaded into the heat conduction model to complete the construction of the finite element simulation equation set. The model has complete material properties, heat source distribution, and boundary effect inputs. It can complete the simulation calculation of the temperature field evolution process of the energy meter box under typical operating conditions in a commercial finite element platform, providing data support for subsequent risk analysis and structural optimization.

[0105] Preferably, setting simulation boundary conditions according to the operating environment of the electric energy meter box includes:

[0106] According to Newton's cooling law, a convection heat transfer Robin boundary condition is applied to the outer surface of the electric energy meter box; the boundary heat flux density of the convection heat transfer Robin boundary condition is defined as q conv (t) = h(t)[T surf (t)-T env (t)]; T surf (t) is the instantaneous temperature of the shell surface, where the heat transfer coefficient h(t) is determined according to the following criteria:

[0107] When the ambient temperature T env ≤35℃ and temperature gradient When the natural convection coefficient h nat =5~10W / (m 2 K);

[0108] When T env >35℃ and When the forced convection coefficient h forced =20~50W / (m 2 K);

[0109] If the relative humidity inside the metering box RH(t) ≥ 60%, use the formula Corrected natural convection coefficient and forced convection coefficient; where h0 is the base heat transfer coefficient, take h nat or h forced The current value of , β is the humidity sensitivity coefficient;

[0110] When the electric energy meter box is in an outdoor solar radiation environment, a composite radiation boundary condition is applied based on plane radiation and the Stefan-Boltzmann law. The heat flux density per unit area under the composite radiation boundary condition is calculated as follows: Among them, q rad (t) is the radiation heat flux density per unit area, η is the solar radiation absorption rate, G solar (t) is the solar irradiance, ∈ is the surface emissivity, and σ' is the Stefan-Boltzmann constant, which is 5.67×10 -8 ;T sky (t) is the equivalent radiation temperature of the sky;

[0111] q conv (t) and q rad (t) A Neumann-type or Robin-type heat flux boundary is loaded onto the outer surface of the finite element numerical calculation model and used as the boundary input for solving the temperature field.

[0112] In this embodiment, in order to truly simulate the heat exchange process between the energy meter box and its external environment, convection heat transfer boundary conditions are first applied to each surface of the energy meter box shell. This heat transfer boundary is based on Newton's law of cooling, that is, the heat flux density is calculated by the heat transfer coefficient and the temperature difference between the surface and the environment. In the specific setting, the system will automatically determine the heat exchange mechanism based on the external ambient temperature and the temperature distribution inside the box: when the external temperature is low and the temperature difference is small, the natural convection mechanism is selected, and the heat transfer coefficient is set to 5 to 10 watts per square meter per Kelvin; when the external temperature is high or the temperature difference is significant, the forced convection mechanism is used instead, and the heat transfer coefficient is increased to 20 to 50 watts per square meter per Kelvin. This boundary setting method can effectively reflect the differences in heat dissipation capacity under different ventilation conditions, ensuring that the temperature field simulation is close to the actual operating environment.

[0113] In some high-humidity environments, the inside of the electricity meter box may be in a high-humidity working state. In order to improve the accuracy of the simulation model in such scenarios, this embodiment introduces a coupled correction mechanism of humidity-heat transfer coefficient. Specifically, when the relative humidity inside the metering box reaches or exceeds 60%, the heat transfer coefficient will no longer use a fixed value, but will be dynamically adjusted as the humidity changes. This adjustment is based on a correction factor, which refers to the current humidity change rate and multiplies it by the sensitivity coefficient and is applied to the basic heat transfer coefficient, thereby amplifying or weakening the natural convection coefficient or the forced convection coefficient. Humidity data can be obtained through temperature and humidity sensors arranged in the box, and its rate of change is calculated in real time by the system through a differential algorithm, thereby supporting automatic correction of the dynamic heat transfer coefficient.

[0114] When the electricity meter box is in an outdoor environment, especially in an area with strong sunlight, its shell will be affected by both solar radiation and sky back radiation. In order to accurately model this process, this embodiment sets a composite radiation heat transfer boundary condition on the surface of the simulation model shell. This condition consists of two parts: one is the heat flux caused by direct sunlight, the size of which depends on the shell's ability to absorb solar energy and the solar irradiance at the time; the other is the infrared radiation released by the sky environment to the surface of the box, which is calculated through common thermal radiation theory and involves parameters such as surface emissivity and sky equivalent radiation temperature. After the above two types of heat flux are combined, a total heat input per unit area is formed, which is applied to the outer surface of the finite element model through standard boundary condition loading as an external heat flux input for temperature field solution. The boundary type can be set to a fixed heat flow type or a mixed heat transfer type as needed, which is automatically identified and processed by the simulation software platform.

[0115] Preferably, based on the finite element numerical calculation model and the simulation boundary conditions, a regional grid division strategy and an adaptive time step algorithm are adopted to perform a temperature field transient simulation, and output a temperature field distribution diagram and abnormal hot spot warning results inside the electric energy meter box, including:

[0116] A tetrahedron encrypted grid is used in the area of ​​the key heating element; the grid characteristic size h of the tetrahedron encrypted grid is fine ≤0.5mm;

[0117] A hexahedral sparse and dense grid is used in the housing and insulating support frame area of ​​the electric energy meter box; the grid characteristic size h of the hexahedral sparse and dense grid is coarse ≥2mm;

[0118] The initial time step Δt0 is set and it is iteratively updated according to the adaptive time step algorithm; the expression of the adaptive time step algorithm is: Among them, ε T is the temperature variation tolerance, Δt max is the maximum allowed time step, Δt n+1 is the time step between step n and step n+1, T i is the instantaneous temperature of node i at the current time step,

[0119] Solve the discretized unsteady heat conduction equations in each time step; the discretized unsteady heat conduction equations are And the energy residual convergence criterion is adopted Determine the iterative convergence; where C is the heat capacity matrix, K(T) is the temperature-dependent thermal conductivity matrix, and Q n+1 is the comprehensive heat source load vector at time step n+1, R E is the energy residual, ε Eis the energy residual tolerance, T n is the temperature vector of all discrete nodes at the nth time step, and t is the time;

[0120] After the simulation is completed, the result field is post-processed to generate the temperature field distribution diagram T(x, y, z, t end ), and calculate the temperature extremes of all nodes. If T i ≥T limit or The corresponding unit is marked as an abnormal hotspot and the abnormal hotspot warning result is output; wherein, T limit is the upper limit of component safety temperature, γ crit is the preset temperature rise rate warning threshold, t end is the endpoint timestamp of the entire time advancement process, x, y, and z are the x-axis coordinate, y-axis coordinate, and z-axis coordinate of the three-dimensional space position respectively;

[0121] The temperature field distribution map and the abnormal hot spot warning results are used as simulation outputs for subsequent operation and maintenance decision-making.

[0122] In this embodiment, in order to ensure that both accuracy and computational efficiency are taken into account during the temperature field simulation process, a regional grid division strategy is adopted for different areas inside the electric energy meter box. In the key heating component areas, such as the electric energy meter chip, circuit breaker contacts and copper busbar connection nodes, a tetrahedral grid with a smaller unit size is used for encryption division, so that the simulation can capture the temperature gradient details of these high heat flux density areas. The unit side length of this area is generally set at the sub-millimeter level, usually between 0.5 mm and 1 mm. For structures with relatively slow thermal changes, such as the outer shell and the insulating support frame area, a sparse grid arrangement of a hexahedral structure is adopted, and the unit size can be set to 2 to 5 mm to form a transition area from dense to sparse. The above division method is implemented by an automatic grid generation tool and adjusted by local encryption control parameters to ensure that the local high thermal sensitivity area has sufficient resolution capability.

[0123] In order to accurately simulate the temperature change trend of the electric energy meter box over time during actual operation, this embodiment adopts an adaptive time step algorithm for transient simulation control. In the initial stage of the simulation, a smaller time step is set as the starting value. In the subsequent calculation process, the time step size is dynamically adjusted according to the size of the temperature change rate in each step, so as to improve the calculation efficiency while ensuring the stability of the calculation. If the temperature of a certain node changes dramatically within a unit time, this embodiment will automatically shorten the time step; if the overall temperature field changes smoothly, the step size will be appropriately lengthened. In each time step, this embodiment is solved based on the temperature results of the previous step, the heat capacity of the material, the thermal conductivity and the heat source distribution, to construct the transient temperature response equation, and iteratively solve the temperature of each node. When the energy residual value is lower than the preset convergence threshold, the current time step solution is completed and the next cycle is entered.

[0124] After the simulation is completed, this embodiment will automatically post-process the temperature field results of all time steps. First, the temperature data at the end time is converted into a three-dimensional temperature distribution diagram, and visualized in the simulation post-processing module. Subsequently, this embodiment analyzes the temperature values ​​of all calculation nodes to identify the maximum temperature point and the fastest changing point. If the temperature of a node exceeds the set safety upper limit, or the temperature rise rate per unit time exceeds the preset threshold, the area will be marked as an abnormal hot spot area, and the early warning mechanism will be triggered. Each abnormal area will be given spatial location information and temperature rise data, and compared with the complete temperature distribution Figure 1 The same output is used for subsequent operation maintenance, structural optimization and fault prevention analysis.

[0125] The beneficial effects of the present invention are as follows:

[0126] (1) The present invention constructs a three-dimensional structural model that takes into account the asymmetric layout of internal components and the thermal parameters of composite materials, and combines it with the setting of multi-material properties to achieve high-fidelity modeling of the actual structure and thermal conduction behavior of the electricity metering box, which can truly reflect the temperature evolution process under complex working conditions.

[0127] (2) The present invention constructs a dynamic heating power data set that evolves over time by performing real-time current sampling, harmonic decomposition, and temperature-related resistivity calculation on key heating elements, which significantly improves the accuracy and dynamic response capability of heat source modeling and effectively solves the problems of large errors and strong hysteresis in traditional static heat source modeling.

[0128] (3) The present invention introduces electromagnetic induction heat source terms and interface thermal resistance modeling, and integrates Fourier's law and energy conservation equation to construct a three-dimensional unsteady-state heat conduction model. Combined with regional grid division and adaptive time step control, the numerical stability of temperature field simulation and the ability to capture local hotspots are significantly improved.

[0129] (4) By simulating and outputting temperature field distribution maps and abnormal hotspot warning results, the present invention can identify the risk of local overheating of the structure in advance, provide reliable data support and decision-making basis for the structural optimization, operation and maintenance, and safety assessment of the electricity meter box, and has significant engineering application value.

[0130] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0131] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A finite element-based temperature field simulation analysis method for an electric energy meter box, characterized in that: include: Constructing a three-dimensional structural model of the electric energy meter box; the structural model is based on the asymmetric spatial layout of internal components of the electric energy meter box and composite material thermal parameter modeling; The internal components include an electric energy meter, a circuit breaker, a copper busbar connector and an insulating support frame; Identifying key heating elements among the internal elements as heat source calculation objects, and calculating resistance losses based on structural parameters, current load data, and harmonic distortion rate of the key heating elements to form a dynamic heating power data set; The dynamic heat generation power distribution is used as a non-uniform heat source input, and a three-dimensional non-steady-state heat conduction differential equation inside the electric energy meter box is established in combination with Fourier's law and the energy conservation equation; Taking the three-dimensional unsteady-state heat conduction differential equation and the dynamic heating power data set as input, a finite element numerical calculation model for temperature simulation is constructed; Setting simulation boundary conditions according to the operating environment of the electric energy meter box; Based on the finite element numerical calculation model and the simulation boundary conditions, a regional grid division strategy and an adaptive time step algorithm are adopted to perform temperature field transient simulation, and output a temperature field distribution map and abnormal hot spot warning results inside the electric energy meter box.

2. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 1 is characterized in that: The key heating components include the energy meter chip, circuit breaker contacts and copper busbar connection nodes.

3. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 1 is characterized in that: Construct a 3D structural model of the electric energy meter box, including: Extracting the geometric dimensions and structural configuration of the housing of the electric energy meter box and determining the properties of the double-layer material used for the housing; the double-layer material properties include the thermal conductivity, thickness, and cavity spacing of the inner aluminum alloy layer and the outer polycarbonate layer; Obtaining the three-dimensional coordinates and installation parameters of the internal components based on the design drawings; the installation parameters include the installation position, connection relationship and spatial arrangement of the electric energy meter, circuit breaker, copper busbar connector and insulation support frame; Establishing a geometric model of each of the internal components in a three-dimensional modeling software, and setting thermophysical parameters according to the material of each of the internal components; the thermophysical parameters include thermal conductivity, density and specific heat capacity; The geometric models are assembled to generate an initial structural model of an electric energy metering box with an asymmetric spatial layout, and the initial structural model is imported into a finite element simulation platform for model verification and mesh division preprocessing to obtain the three-dimensional structural model.

4. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 2, characterized in that: Identify key heating elements among the internal elements as heat source calculation objects, and calculate resistance losses based on structural parameters, current load data, and harmonic distortion rate of the key heating elements to form a dynamic heating power data set, including: Perform real-time current sampling on the electric energy meter chip, the circuit breaker contacts and the copper busbar connector to obtain the fundamental wave effective value I1 and the effective value of each order harmonic I h ; Extracting the wire length L and cross-sectional area A of each key heating element as input of the structural parameters; According to the real-time temperature T, the resistivity is calculated using the temperature-dependent resistivity function; the expression of the temperature-dependent resistivity function ρ(T) is: ρ(T) = ρ 20 [1+γ·(T-20)]; where ρ 20 is the base resistivity of the conductor at 20°C, γ is the temperature coefficient of resistance; T is the temperature field variable; The weighted coefficient of the harmonic correction factor is calculated according to the frequency weight formula; the frequency weight formula is: Among them, w h is the frequency weight coefficient corresponding to the h-th order harmonic, α is the frequency attenuation factor, ranging from 0.5 to 1.5, n is the highest order considered in the harmonic analysis, and k is the harmonic order variable that participates in the accumulation in the weight normalization calculation; And according to the formula Calculate the harmonic correction factor; where κ is the harmonic correction factor; Based on the formula Calculate the resistance loss power density q; where A is the cross-sectional area of ​​the conductor; The resistance loss power density q is mapped to the node area corresponding to the key heating components in the three-dimensional structural model to form a dynamic heating power data set that changes with time.

5. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 1, characterized in that: The dynamic heat generation power distribution is used as a non-uniform heat source input, and combined with Fourier's law and the energy conservation equation, a three-dimensional unsteady-state heat conduction differential equation inside the electric energy meter box is established, including: Mapping the dynamic heating power data set into a non-uniform internal heat source term Q(x, y, z, t) and embedding it into the corresponding node in the three-dimensional structural model; where x, y, and z are the x-axis coordinates, y-axis coordinates, and z-axis coordinates of the three-dimensional spatial position, respectively, and t is time; According to Fourier's law expression Construct a local relationship between heat flux and temperature gradient; where λ(T) is the temperature-dependent thermal conductivity, is the heat flux vector, is the temperature gradient; According to the energy conservation equation, the non-uniform internal heat source term Q(x, y, z, t) and the local relationship are combined to establish the unsteady three-dimensional heat conduction differential equation: Where ρ is the material density, c p is the material's specific heat capacity at constant pressure, and T is the temperature field variable; Set the material area attributes and assign different thermal physical parameters to different component areas; the thermal physical parameters include ρ, c p , λ(T) to realize temperature field modeling under heterogeneous material conditions.

6. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 5, characterized in that: The three-dimensional unsteady-state heat conduction differential equation and the dynamic heating power data set are used as input to construct a finite element numerical calculation model for temperature simulation, including: The corresponding thermal conductivity forms are assigned to different material areas in the electric energy meter box structure model, among which the temperature-dependent thermal conductivity scalar λ is set for the isotropic material area. s (T), sets the temperature-dependent thermal conductivity tensor Λ(T) for the anisotropic material region; Introduce the electromagnetic induction heat source term Q in the conductive component area em (x, y, z, t), the electromagnetic induction heat source term Q em (x,y,z,t) including the eddy current loss term Q eddy and the hysteresis loss term Q hyst , the formula is: Q em (x,y,z,t)=Q eddy +Q hyst ; Where σ is the conductivity, ω is the current angular frequency, B is the effective value of the magnetic induction intensity, d is the conductor thickness, k h is the hysteresis coefficient, f is the frequency, B m is the maximum magnetic induction intensity, n is the hysteresis index; An interface thermal resistance model is set at the copper busbar connection node and the circuit breaker contact; the interface thermal resistance model R c The calculation formula is: Where δ is the thickness of the interface gap, λ int is the thermal conductivity of the interface material, R int is the contact thermal resistance constant; The electromagnetic induction heat source term Q em (x, y, z, t) and the interface thermal resistance model are substituted into the three-dimensional unsteady-state heat conduction differential equation to construct a finite element simulation calculation model; the formula of the finite element simulation calculation model is: Among them, Q c (x,y,z,t) is due to R c The equivalent volume heat source term formed by the local temperature difference near the interface caused by c Where ΔT is the temperature difference on both sides of the contact interface, A′ is the area of ​​the thermal contact interface, and V is the local unit volume involved in heat transfer.

7. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 5, characterized in that: The simulation boundary conditions are set according to the operating environment of the electric energy meter box, including: According to Newton's cooling law, a convection heat transfer Robin boundary condition is applied to the outer surface of the electric energy meter box; the boundary heat flux density of the convection heat transfer Robin boundary condition is defined as q conv (t) = h(t)[T surf (t)-T env (t)]; T surf (t) is the instantaneous temperature of the shell surface, where the heat transfer coefficient h(t) is determined according to the following criteria: When the ambient temperature T env ≤35℃ and temperature gradient When the natural convection coefficient h nat =5~10W / (m 2 K); When T env >35℃ and When the forced convection coefficient h forced =20~50W / (m 2 K); If the relative humidity inside the metering box RH(t) ≥ 60%, use the formula Corrected natural convection coefficient and forced convection coefficient; where h0 is the base heat transfer coefficient, take h nat or h forced The current value of , β is the humidity sensitivity coefficient; When the electric energy meter box is in an outdoor solar radiation environment, a composite radiation boundary condition is applied based on plane radiation and the Stefan-Boltzmann law. The heat flux density per unit area under the composite radiation boundary condition is calculated as follows: Among them, q rad (t) is the radiation heat flux density per unit area, η is the solar radiation absorption rate, G solar (t) is the solar irradiance, ∈ is the surface emissivity, and σ' is the Stefan-Boltzmann constant, which is 5.67×10 -8 ;T sky (t) is the equivalent radiation temperature of the sky; q conv (t) and q rad (t) A Neumann-type or Robin-type heat flux boundary is loaded onto the outer surface of the finite element numerical calculation model and used as the boundary input for solving the temperature field.

8. The finite element-based temperature field simulation analysis method for an electric energy meter box according to claim 1, characterized in that: Based on the finite element numerical calculation model and the simulation boundary conditions, a regional grid division strategy and an adaptive time step algorithm are adopted to perform a temperature field transient simulation, and output a temperature field distribution diagram inside the electric energy meter box and abnormal hot spot warning results, including: A tetrahedron encrypted grid is used in the area of ​​the key heating element; the grid characteristic size h of the tetrahedron encrypted grid is fine ≤0.5mm; A hexahedral sparse and dense grid is used in the housing and insulating support frame area of ​​the electric energy meter box; the grid characteristic size h of the hexahedral sparse and dense grid is coarse ≥2mm; The initial time step Δt0 is set and it is iteratively updated according to the adaptive time step algorithm; the expression of the adaptive time step algorithm is: Among them, ε T is the temperature variation tolerance, Δt max is the maximum allowed time step, Δt n+1 is the time step between step n and step n+1, T i is the instantaneous temperature of node i at the current time step, Solve the discretized unsteady heat conduction equations in each time step; the discretized unsteady heat conduction equations are And the energy residual convergence criterion is adopted Determine the iterative convergence; where C is the heat capacity matrix, K(T) is the temperature-dependent thermal conductivity matrix, and Q n+1 is the comprehensive heat source load vector at time step n+1, R E is the energy residual, ε E is the energy residual tolerance, T n is the temperature vector of all discrete nodes at the nth time step, and t is the time; After the simulation is completed, the result field is post-processed to generate the temperature field distribution diagram T(x, y, z, t end ), and calculate the temperature extremes of all nodes. If T i ≥T limit or The corresponding unit is marked as an abnormal hotspot and the abnormal hotspot warning result is output; wherein, T limit is the upper limit of component safety temperature, γ crit is the preset temperature rise rate warning threshold, t end is the endpoint timestamp of the entire time advancement process, x, y, and z are the x-axis coordinate, y-axis coordinate, and z-axis coordinate of the three-dimensional space position respectively; The temperature field distribution map and the abnormal hot spot warning results are used as simulation outputs for subsequent operation and maintenance decision-making.

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