Electromagnetic interference suppression method, device and equipment for high-efficiency connector

Abstract

The invention provides an electromagnetic interference suppression method, device and equipment for a high-efficiency connector. The method comprises the following steps: determining electromagnetic field distribution data of the high-efficiency connector according to a simulation model of the high-efficiency connector; determining material characteristic parameters of the composite material under the electromagnetic field distribution data through multi-physical field coupling analysis; generating a shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material characteristic parameters; determining impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material characteristic parameters; detecting an interference signal characteristic of the interference signal according to the impedance characteristic parameter; and dynamically adjusting filter parameters through the interference signal characteristics, and performing interference suppression on the interference signal. Through the implementation of the scheme of the invention, the impedance characteristic parameters are utilized, the interference signal characteristics are accurately detected, the filter parameters are dynamically adjusted through the interference signal characteristics, interference suppression is carried out on the interference signals, and the precision and efficiency of electromagnetic interference suppression are improved.

Description

Technical Field

[0001] This application relates to the field of signal processing, and particularly to an electromagnetic interference suppression method, device, and equipment for an efficient connector. Background Art

[0002] With the development of electronic devices towards high speed, miniaturization, and high frequency, the problem of electromagnetic interference (EMI) has become increasingly serious, becoming an important factor affecting the performance and reliability of electronic devices. Existing electromagnetic interference suppression methods mainly rely on traditional means such as shielding technology, filtering technology, and grounding technology. These methods have many deficiencies in practical applications. First, traditional shielding technologies usually use metal shielding cases or coated conductive materials. Although these methods can shield electromagnetic interference to a certain extent, due to the lack of pertinence in design, they often cannot effectively cope with complex and changing electromagnetic environments, and the shielding effect is limited. Second, filtering technologies usually use filters with fixed parameters, such as low-pass filters, high-pass filters, etc. These filters have fixed frequency response characteristics in design, lack flexibility, and cannot be dynamically adjusted to adapt to interference signals of different frequencies and intensities, resulting in unsatisfactory suppression effects in practical applications. In addition, grounding technology eliminates interference signals by connecting the system to the ground, but due to the difficulty in precisely controlling parameters such as the resistance and inductance of the grounding system, the actual effect often fails to meet expectations. Existing methods also generally ignore the particularity of efficient connectors. Especially in high-speed data transmission scenarios, the impedance matching problem of connectors has an important impact on signal integrity and transmission efficiency. Due to the lack of precise control of impedance characteristics, existing methods are prone to signal reflection and crosstalk, and instead become new interference sources. Summary of the Invention

[0003] This application provides an electromagnetic interference suppression method, device, and equipment for an efficient connector, which is used to solve the problem in related technologies that electromagnetic interference signals cannot be precisely suppressed.

[0004] In the first aspect of this application, an electromagnetic interference suppression method for an efficient connector is provided. The electromagnetic interference suppression method for the efficient connector includes: Determine the electromagnetic field distribution data of the efficient connector according to the simulation model of the efficient connector; Determine the material property parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis; Generate the shielding structure of the efficient connector according to the electromagnetic field distribution data and the material property parameters; Determine the impedance characteristic parameters of the efficient connector according to the geometric parameters of the shielding structure and the material property parameters; Detect the interference signal characteristics of the interference signal according to the impedance characteristic parameters; The filter parameters are dynamically adjusted according to the interference signal characteristics to suppress the interference signal.

[0005] Optionally, in the first implementation manner of the first aspect of this application, the step of determining the electromagnetic field distribution data of the high-efficiency connector according to the simulation model of the high-efficiency connector includes: Model the geometric structure of the high-efficiency connector to generate a simulation model of the high-efficiency connector; Determine the electromagnetic interference prone area corresponding to the high-efficiency connector in the simulation model; Determine the electromagnetic field distribution data of the electromagnetic interference prone area through frequency domain scanning.

[0006] Optionally, in the second implementation manner of the first aspect of this application, the electromagnetic field distribution data includes electromagnetic field strength and energy distribution data. The step of determining the material characteristic parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis includes: Construct a numerical model of the material microstructure according to the electromagnetic field strength and the energy distribution data; Carry out electromagnetic performance simulation on the numerical model of the material microstructure through multi-physics field coupling analysis; Simulate the random distribution characteristics of material parameters by the Monte Carlo method; Determine the material characteristic parameters of the composite material according to the simulation results of the electromagnetic performance simulation and the random distribution characteristics.

[0007] Optionally, in the third implementation manner of the first aspect of this application, after the step of generating the shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material characteristic parameters, it further includes: Determine the shielding effectiveness of the shielding structure; Obtain the thermal effect data of the shielding structure during high-frequency signal transmission; Optimize the shielding structure according to the shielding effectiveness and the thermal effect data.

[0008] Optionally, in the fourth implementation manner of the first aspect of this application, the step of determining the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material characteristic parameters includes: Generate an impedance matching network according to the impedance characteristic parameters; Optimize the impedance characteristic parameters at different signal transmission frequencies through an intelligent matching algorithm in the impedance matching network; Optimize the impedance matching network according to the optimized impedance characteristic parameters and the thermal effect data.

[0009] Optionally, in the fifth implementation manner of the first aspect of the present application, the method further includes: Predicting the interference mode of electromagnetic interference according to the matching network parameters of the impedance matching network; Generating a control strategy for suppressing interference according to the interference signal characteristics and the interference mode; Adjusting the matching network parameters and the filter parameters through the control strategy to perform real-time suppression of the interference signal.

[0010] Optionally, in the sixth implementation manner of the first aspect of the present application, the method further includes: Detecting the interference suppression effect of the control strategy; Analyzing the difference in the suppression effect by comparing the interference suppression effect with historical interference data; Adjusting the filter parameters and the matching network parameters according to the difference in the suppression effect.

[0011] The second aspect of the present application provides an electromagnetic interference suppression device for a high-efficiency connector, and the electromagnetic interference suppression device for the high-efficiency connector includes: A first determination module, configured to determine the electromagnetic field distribution data of the high-efficiency connector according to the simulation model of the high-efficiency connector; A second determination module, configured to determine the material property parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis; A generation module, configured to generate a shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material property parameters; A third determination module, configured to determine the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material property parameters; A detection module, configured to detect the interference signal characteristics of the interference signal according to the impedance characteristic parameters; A control module, configured to dynamically adjust the filter parameters through the interference signal characteristics to perform interference suppression on the interference signal.

[0012] The third aspect of the embodiments of the present application provides an electronic device, including a memory and a processor, wherein the processor is configured to execute a computer program stored on the memory, and when the processor executes the computer program, the steps in the electromagnetic interference suppression method for the high-efficiency connector provided in the first aspect of the embodiments of the present application are implemented.

[0013] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the electromagnetic interference suppression method for the high-efficiency connector provided in the first aspect of the embodiments of the present application are implemented.

[0014] In summary, according to an electromagnetic interference suppression method, device, and equipment for an efficient connector provided by the solution of the present application, electromagnetic field distribution data of the efficient connector is determined based on a simulation model of the efficient connector; material property parameters of a composite material are determined through multi-physics field coupling analysis under the electromagnetic field distribution data; a shielding structure of the efficient connector is generated based on the electromagnetic field distribution data and the material property parameters; impedance characteristic parameters of the efficient connector are determined based on geometric parameters of the shielding structure and the material property parameters; interference signal characteristics of an interference signal are detected based on the impedance characteristic parameters; and filter parameters are dynamically adjusted through the interference signal characteristics to suppress the interference signal. Through the implementation of the solution of the present application, by using impedance characteristic parameters, interference signal characteristics are accurately detected, and through the interference signal characteristics, filter parameters are dynamically adjusted to suppress the interference signal, improving the accuracy and efficiency of electromagnetic interference suppression. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic flowchart of an electromagnetic interference suppression method for an efficient connector provided by an embodiment of the present application; Figure 2 is a schematic diagram of program modules of an electromagnetic interference suppression device for an efficient connector provided by an embodiment of the present application; Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] To make the objectives, features, and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present application.

[0017] To solve the problem in the related art that electromagnetic interference signals cannot be accurately suppressed, an embodiment of the present application provides an electromagnetic interference suppression method for an efficient connector, as Figure 1 shown in the schematic flowchart of the electromagnetic interference suppression method for an efficient connector provided by this embodiment. The electromagnetic interference suppression method for the efficient connector includes the following steps: Step 110: Determine electromagnetic field distribution data of the efficient connector based on a simulation model of the efficient connector.

[0018] Specifically, in this embodiment, a suitable electromagnetic simulation software is selected. For example, HFSS (High Frequency Structure Simulator) is used for simulation. HFSS is a software widely used in electromagnetic field analysis and can simulate the electric and magnetic field distributions of high-frequency electronic devices. The specific structural parameters of the high-efficiency connector, including information such as dimensions, shapes, and materials, are input into HFSS to create a geometric model of the high-efficiency connector. The boundary conditions and excitation sources required for the simulation are set. For example, a voltage signal is applied to the input end of the connector, and the output end is set to match the load impedance. The simulation program is run to calculate the electromagnetic field distribution. The software will obtain the electromagnetic field distribution data inside and around the connector through the finite element method or other numerical calculation methods based on the input model and parameters.

[0019] In an alternative embodiment of this embodiment, the steps of determining the electromagnetic field distribution data of the high-efficiency connector according to the simulation model of the high-efficiency connector include: modeling the geometric structure of the high-efficiency connector to generate a simulation model of the high-efficiency connector; determining the electromagnetic interference prone areas corresponding to the high-efficiency connector in the simulation model; and determining the electromagnetic field distribution data of the electromagnetic interference prone areas through frequency domain scanning.

[0020] Specifically, in this embodiment, the finite element method (FEM) is a powerful numerical calculation method. It can decompose complex geometric structures into many small finite elements and obtain the overall field distribution by solving the field quantities of each element. For the high-efficiency connector, first, detailed geometric information needs to be obtained, including dimensions, shapes, and the electromagnetic properties of each part of the material. Then, electromagnetic simulation software can be used for modeling. The specific dimensions and shape information of the connector are input into the electromagnetic simulation software, and the material properties of each part are defined, such as conductivity, permittivity, and permeability. After that, the geometric model is meshed, and the entire geometric model is decomposed into many small finite elements. Each element can be a triangle, quadrilateral, or other simple shapes. After generating the simulation model, boundary conditions and excitation sources need to be set in the model. The boundary conditions are used to describe the interaction between the model and the outside world, such as open circuit, short circuit, or radiation boundary, etc. The excitation source is used to simulate the signal input in actual operation, such as applying a sinusoidal voltage source or current source. After setting these conditions, the simulation calculation can be carried out. The simulation software will gradually iterate to obtain the electromagnetic field distribution of the entire model by solving the electromagnetic field quantities of each finite element according to the principle of the finite element method.

[0021] Regions prone to electromagnetic interference are usually areas with relatively high electromagnetic field intensities. These regions are vulnerable to external electromagnetic interference or generate electromagnetic radiation. By observing the electric and magnetic field distribution maps in the simulation results, the distribution of electromagnetic field intensities can be visually seen. In regions with high electric field intensities, they are often hotspots for electromagnetic interference. The post-processing function in the simulation software can be used to conduct a detailed analysis of the electric and magnetic field distributions to determine the specific locations and extents of regions prone to electromagnetic interference. Frequency-domain scanning refers to performing simulation calculations at different frequencies to obtain electromagnetic field distribution data at each frequency point. Frequency-domain scanning can help identify the changes in the electromagnetic fields in regions prone to electromagnetic interference at different operating frequencies. Set the frequency range and step size for frequency-domain scanning. For example, conduct simulation calculations every 100 MHz within the range from 1 GHz to 10 GHz. The simulation software will automatically perform calculations at these frequency points and generate corresponding electromagnetic field distribution data. The electromagnetic field distribution data obtained through frequency-domain scanning can be used for further analysis of the frequency characteristics and propagation paths of electromagnetic interference. In this data, it can be observed that at certain specific frequencies, the electric and magnetic field intensities in regions prone to electromagnetic interference will increase significantly. These frequencies are often resonance frequencies and are prone to generating electromagnetic interference. By analyzing the electromagnetic field distributions at these frequency points, the main sources and propagation paths of interference can be determined, thereby taking effective shielding and suppression measures.

[0022] Step 120: Determine the material property parameters of the composite material under the electromagnetic field distribution data through multi-physics coupling analysis.

[0023] Specifically, in this embodiment, a suitable multi-physics simulation software is selected. For example, COMSOL Multiphysics (a multi-physics simulation software) is used for simulation. COMSOL is a powerful multi-physics simulation software that can handle the coupling problems of multiple physical fields including electromagnetic fields, thermal fields, and structural mechanics. Import the electromagnetic field distribution data into COMSOL and set the initial properties of the composite material in COMSOL, including dielectric constant, conductivity, permeability, etc. Set the coupling conditions between the electromagnetic field and other physical fields. For example, set the coupling between the electromagnetic field and the thermal field, considering the thermal effect caused by electromagnetic loss; or set the coupling between the electromagnetic field and the force field, considering the influence of electromagnetic force on the material properties. Run the coupling analysis simulation. The software will, based on the input data and conditions, obtain the steady-state material property parameters of the composite material under the action of the electromagnetic field through iterative calculations.

[0024] In an optional implementation manner of this embodiment, the electromagnetic field distribution data includes electromagnetic field intensity and energy distribution data. The steps of determining the material characteristic parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis include: constructing a numerical model of the material microstructure according to the electromagnetic field intensity and energy distribution data; performing electromagnetic performance simulation on the numerical model of the material microstructure through multi-physics field coupling analysis; simulating the random distribution characteristics of the material parameters by the Monte Carlo method; and determining the material characteristic parameters of the composite material according to the simulation results of the electromagnetic performance simulation and the random distribution characteristics.

[0025] Specifically, in this embodiment, based on the obtained electromagnetic field intensity data and energy distribution data, a microscopic structure model of the material is established using multi-physics field simulation software. After the numerical model of the microstructure is constructed, electromagnetic performance simulation is performed on the numerical model of the material microstructure through multi-physics field coupling analysis. Multi-physics field coupling analysis refers to coupling multiple physical fields (such as electromagnetic field, thermal field, force field, etc.) together for joint simulation. When performing electromagnetic performance simulation on the basis of the numerical model of the material microstructure, the response of the material in the electromagnetic field needs to be considered, and at the same time, the influence of other physical fields needs to be considered. For example, the change in the electromagnetic field may cause a change in the temperature of the material, which in turn affects the electromagnetic performance of the material. Therefore, through multi-physics field coupling analysis, the electromagnetic performance of the material can be more accurately simulated, and more realistic simulation results can be obtained.

[0026] Then, the random distribution characteristics of the material parameters are simulated by the Monte Carlo method. The Monte Carlo method is a numerical simulation method based on random sampling and can be used to simulate systems with randomness or uncertainty. In materials science, the microstructure and parameters of materials usually have randomness, such as particle size, shape, distribution, and material composition. Through the Monte Carlo method, these random characteristics can be simulated to generate a large number of numerical models of the material microstructure with different parameters. These models can reflect the random distribution characteristics of the material parameters. Through the previous multi-physics field coupling analysis and Monte Carlo simulation, a large number of electromagnetic performance simulation results under different parameters can be obtained. These results can be used to analyze the electromagnetic performance of the composite material under various conditions. Combining the random distribution characteristics of the material parameters, the material characteristic parameters of the composite material can be determined by statistical analysis methods.

[0027] Optionally, for example, assume that it is necessary to analyze the electromagnetic shielding performance of a composite material containing ferromagnetic particles. First, through experiments or numerical simulations, obtain the electromagnetic field strength and energy distribution data of the material in electromagnetic fields of different frequencies. Then, based on these data, construct a numerical model of the material's microstructure, including the size, shape of the ferromagnetic particles, and their distribution in the matrix. Next, through multi-physics coupling analysis, simulate the electromagnetic shielding performance of the material in electromagnetic fields of different frequencies. At this time, it is necessary to consider the magnetization response of the ferromagnetic particles in the electromagnetic field and its impact on the overall electromagnetic properties of the material. After that, through the Monte Carlo method, simulate the random distribution characteristics of the ferromagnetic particle parameters, and generate a large number of material models with different particle distributions. Finally, combining the simulation results and the random distribution characteristics, statistically analyze the electromagnetic shielding performance parameters of the material, such as the average value and standard deviation of the shielding effectiveness, etc., so as to determine the electromagnetic shielding performance of the composite material under different conditions.

[0028] It should be noted that the energy distribution data includes but is not limited to electromagnetic energy distribution (the distribution of electromagnetic energy inside or on the surface of the material under the action of an electromagnetic field), thermal energy distribution (the spatial distribution of thermal energy in the material under the action of a temperature field), and mechanical energy distribution (the spatial distribution of mechanical energy in the material under the action of a mechanical load). Combining the energy distribution data, the formula for the numerical model of the material microstructure can be expressed as: , where M represents the numerical model of the material microstructure, E is the electric field strength vector, H is the magnetic field strength vector, T is the temperature distribution, is the conductivity tensor of the material, is the permeability tensor of the material, , , respectively represent the distributions of electromagnetic energy, thermal energy, and mechanical energy.

[0029] Next, the process of simulating the electromagnetic properties of the numerical model of the material microstructure through multi-physics coupling analysis can be expressed as: , where P represents the simulation result of the electromagnetic properties, is the acting force of the electromagnetic field, is the acting force of the thermal field, is the acting force of the force field. The function represents the process of multi-physics coupling analysis. Then, the random distribution characteristics of the material parameters are simulated through the Monte Carlo method, and this process can be expressed as: , where S represents the random distribution characteristics of the material parameters, is the electromagnetic performance result of the j-th simulation, is the probability density function of the material parameters in the jth simulation, and K is the total number of Monte Carlo simulations. Function h represents the process of processing each simulation result. Finally, the material characteristic parameters of the composite material are determined based on the electromagnetic performance simulation results and random distribution characteristics. This process can be expressed as: , Among them, C represents the material characteristic parameters of the composite material, X is the value range of the material parameter, and the function Represents the process of determining material characteristic parameters based on random distribution characteristics.

[0030] It is understandable that energy distribution data can reveal the inhomogeneity of the microstructure inside the material. Actual materials often have complex microstructures, such as grains, phase interfaces, defects, etc., and the distribution of these microstructures in different regions is uneven. Energy distribution data can reflect these inhomogeneities and reveal the local characteristics inside the material. For example, electromagnetic energy distribution can reveal the difference in response of different phases or different grains in the material in the electromagnetic field; thermal energy distribution can reflect the local changes in thermal conductivity in the material; mechanical energy distribution can reveal the local characteristics of stress concentration and deformation in the material. Through these energy distribution data, a more accurate numerical model of the microstructure can be constructed.

[0031] Step 130: Generate a shielding structure of a high-efficiency connector according to the electromagnetic field distribution data and material characteristic parameters.

[0032] Specifically, in this embodiment, the electromagnetic field distribution data and material characteristic parameters are imported into the HFSS software, and the areas that need to be shielded are determined based on the electromagnetic field distribution data, and appropriate shielding materials are selected based on the material characteristic parameters, and the geometric structure of the shielding layer is designed. Then, the simulation of the shielding structure is run to evaluate the shielding effect, and the shielding structure is optimized and adjusted based on the simulation results, for example, the thickness and shape of the shielding layer are adjusted, or the shielding material is replaced.

[0033] In an optional implementation of the present embodiment, after the step of generating a shielding structure of an efficient connector based on electromagnetic field distribution data and material characteristic parameters, it also includes: determining the shielding effectiveness of the shielding structure; obtaining thermal effect data of the shielding structure during high-frequency signal transmission; and optimizing the shielding structure based on the shielding effectiveness and thermal effect data.

[0034] Specifically, determining the shielding effectiveness of a shielding structure refers to evaluating the ability of a shielding material or structure to suppress electromagnetic interference. Shielding effectiveness is usually measured in decibels (dB) and represents the attenuation ability of the shielding material to electromagnetic waves. In this embodiment, the shielding effectiveness is evaluated through numerical simulation methods. By using electromagnetic simulation software, a model of the shielding structure is established through numerical simulation methods. The process of the propagation and attenuation of electromagnetic waves in the shielding material is calculated through simulation, thereby obtaining the shielding effectiveness. During the process of evaluating the shielding effectiveness, various characteristics of the shielding material need to be considered, including conductivity, permittivity, permeability, etc. These characteristics will affect the reflection, absorption, and conduction abilities of the shielding material to electromagnetic waves, thereby affecting the shielding effectiveness. For example, a metal material with a relatively high conductivity has good reflection ability and can effectively reflect electromagnetic waves, while a material with a relatively high permittivity has a strong absorption ability and can absorb and attenuate electromagnetic waves. Therefore, through experimental measurement or numerical simulation, the shielding effectiveness of different materials and structures can be evaluated, and the optimal shielding solution can be selected.

[0035] During the high-frequency signal transmission process, electromagnetic waves propagating in the shielding material will generate electromagnetic losses, resulting in an increase in the internal temperature of the material. The thermal effect data includes the temperature distribution of the material, heat conduction, and heat dissipation ability, etc. By using thermal simulation software through numerical simulation methods, a thermal model of the shielding structure is established. The heat generated by electromagnetic losses and its conduction and heat dissipation processes in the material are calculated through simulation, thereby obtaining the thermal effect data.

[0036] Optimizing the shielding structure based on the shielding effectiveness and thermal effect data means improving and optimizing the shielding structure on the basis of comprehensively considering the electromagnetic shielding performance and thermal management performance. The goal of optimization is to not only ensure that the shielding structure has good electromagnetic shielding effectiveness but also ensure that it can effectively manage heat during the high-frequency signal transmission process and avoid performance degradation or damage caused by overheating. By simulating and calculating the electromagnetic wave propagation and heat conduction processes, analyzing the shielding effectiveness and thermal effects of different materials and structures, and carrying out optimized design according to the simulation results.

[0037] Step 140: Determine the impedance characteristic parameters of the high-efficiency connector according to the geometric parameter and material characteristic parameter of the shielding structure.

[0038] Specifically, the impedance characteristic parameters refer to the resistance, inductance, capacitance, etc. of the connector at the operating frequency, and these parameters have an important impact on the performance of the connector. In this embodiment, a suitable electromagnetic simulation software or impedance analyzer is selected. For example, an impedance analyzer of Keysight is used for testing, or HFSS is continued to be used for simulation calculation. The geometric parameter and material property parameter of the shielding structure are imported into the software or instrument, including but not limited to the length, width, height, number of layers of the shielding layer, and the material thickness of each layer, etc. At the same time, the simulation or test conditions such as the operating frequency and load conditions of the connector are set. For example, the operating frequency is set to 2.4 GHz and the load is 50 ohms. Run the simulation or conduct actual tests to obtain the impedance characteristic parameters of the connector.

[0039] In an alternative implementation manner of this embodiment, the steps of determining the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters and material property parameters of the shielding structure include: generating an impedance matching network according to the impedance characteristic parameters; optimizing the impedance characteristic parameters at different signal transmission frequencies through an intelligent matching algorithm in the impedance matching network; and optimizing the impedance matching network according to the optimized impedance characteristic parameters and thermal effect data.

[0040] Specifically, in this embodiment, the goal of the impedance matching network is to match the input impedance of the system with the impedance of the signal source or load, thereby minimizing reflections and power losses. The impedance characteristic parameters usually include resistance, inductance, capacitance, etc. These parameters can be obtained through simulation calculations. By selecting an appropriate circuit topology (such as a π-type network, T-type network, etc.) and calculating the values of each component according to the impedance characteristic parameters, a preliminary impedance matching network is generated. Since the high-efficiency connector may operate in a wide frequency band range and the impedance characteristics vary at different frequencies, an intelligent matching algorithm is required to optimize the impedance matching network. Intelligent matching algorithms can adopt genetic algorithms, particle swarm optimization algorithms, etc. These algorithms can search for the optimal solution in a multi-dimensional parameter space. For example, the genetic algorithm gradually optimizes the circuit parameters by simulating the processes of natural selection and genetic variation, so that the impedance matching performance of the system reaches the best in the entire frequency band range. The particle swarm optimization algorithm simulates the behavior of bird flocks foraging and uses the information exchange and cooperation among particles to quickly find the global optimal solution. Through the intelligent matching algorithm, the parameters of each component in the impedance matching network can be automatically adjusted to achieve good impedance matching at different signal transmission frequencies, thereby improving the transmission efficiency and stability of the system. During the process of optimizing the impedance matching network, thermal effect data also needs to be considered. The high-efficiency connector generates heat during operation, and this heat will affect the electrical performance and impedance characteristics of the components. Therefore, when optimizing the impedance matching network, the thermal effect data needs to be taken into account. The thermal effect data can be obtained through thermal simulation software, including the temperature distribution, heat conduction, and heat dissipation capacity of the components. During the optimization process, electromagnetic simulation and thermal simulation can be combined to comprehensively analyze the performance changes of the components at different operating temperatures and adjust the design of the impedance matching network.

[0041] It should be noted that in the process of applying the genetic algorithm to optimize the parameters of the impedance matching network, an initial population needs to be set first. , the population size is N, and the initial population is the starting point of the genetic algorithm and consists of a group of randomly generated individuals. Each individual represents a possible combination of impedance matching network parameters, such as different values of resistance (R), capacitance (C), and inductance (L). Then, the fitness of each individual needs to be evaluated. The fitness function is defined as: , where, represents the i-th individual in the population, m is the number of frequency sample points, k is an index variable representing the number of the frequency sampling point, represents the reflection coefficient at the frequency , is the thermal effect penalty coefficient, is the performance change under the thermal effect, and the fitness function To evaluate the matching performance of each individual, this function takes into account the reflection coefficient and thermal effects. During the optimization process, the smaller the reflection coefficient, the higher the fitness. It ensures that the sum of the reflection coefficients is minimized at different frequency sample points while considering the impact of thermal effects on performance. The thermal effect penalty coefficient ensures that thermal effects are appropriately considered and prevents the optimization results from failing under actual working conditions.

[0042] The selection operation of the genetic algorithm is based on the fitness function value. Through the roulette wheel selection method, individuals with high fitness are more likely to be selected into the next generation. The selection probability is defined as: , where N is the population size, is the index variable, used to calculate the sum of the fitness of all individuals and is the traversal index in the sum. This selection method ensures that individuals with high fitness have a greater chance of passing their parameters to the next generation while maintaining the diversity of the population.

[0043] The crossover operation is used to generate new individuals and adopts the single-point crossover method. Suppose the parent individuals are and , and the crossover point is b. The generated new individuals are: , where n is the number of parameters of each individual, represents that the parent individuals and have a crossover at the b-th parameter position, and the generated new individual directly inherits the parameters of the parent individual at other positions. Usually, is the individual selected with a higher probability during selection (the individual with high fitness), so inheriting 's most features helps maintain the population quality.

[0044] The mutation operation is used to introduce new parameters to prevent the population from falling into local optima. Suppose the k-th parameter of the individual mutates, and the new individual after mutation is: , where, is the mutation intensity coefficient, r is a random number in the range [0, 1], and are the upper and lower limits of the parameter respectively, is the span of the parameter within the allowable range. Generate a random number r, subtract 0.5 to make it fall within the range of [−0.5, 0.5], which means it can vary in both positive and negative directions. After multiplying by the range span, a small amplitude that can vary in both positive and negative directions is obtained, and then multiplied by the coefficient , to control the strength of the variation, The smaller it is, the milder the mutation, avoiding excessive damage to the original structure. Then add it to the original parameter to obtain the new value after mutation. Mutation is to impose a small, controllable, two-way random perturbation on a certain parameter within the allowable range, thereby improving the diversity and search ability of the population.

[0045] Generate a new population through selection, crossover, and mutation operations , repeat the above steps until the stopping condition is reached (such as the number of generations of evolution or the convergence of the fitness function). Through continuous iteration, the algorithm gradually approaches the optimal solution. The optimal solution refers to the parameter combination that maximizes the fitness function within the given conditions and search space. In practical applications, the optimized impedance matching network needs to be experimentally verified for its performance. In the frequency range from 1 GHz to 10 GHz, the optimized network should show a significantly reduced reflection coefficient and a smaller transmission loss. In addition, verify the stability of the optimization results in a high-temperature environment through thermal simulation to ensure its reliability under actual working conditions.

[0046] Step 150: Detect the interference signal characteristics of the interference signal according to the impedance characteristic parameters.

[0047] Specifically, in this embodiment, record the impedance characteristic parameters in the normal working state of the high-speed connector, establish the reference data of the impedance-frequency curve, determine the threshold of the normal change range of the impedance, continuously monitor the system impedance using a vector network analyzer, record the real-time changes of the impedance amplitude and phase, calculate the impedance deviation through the difference between the real-time value and the reference value, analyze the time-domain characteristics of the impedance change, and perform spectral analysis according to the time-domain characteristics to determine the characteristics such as the frequency and intensity of the interference signal.

[0048] Step 160: Dynamically adjust the filter parameters according to the interference signal characteristics to suppress the interference signal.

[0049] Specifically, in this embodiment, a suitable filter is designed according to the characteristics of the interference signal. The type and parameters of the filter need to be selected according to the frequency and amplitude of the interference signal. When designing the filter, parameters such as the center frequency, bandwidth, and filter order need to be considered to ensure that the filter can exhibit the best suppression effect within the target frequency band while minimizing the impact on the transmission of the useful signal. The initially designed filter is tested using electromagnetic field simulation software or actual experiments to evaluate its suppression effect and the impact on the useful signal. According to the test results, parameters such as the center frequency, bandwidth, and filter order of the filter are adjusted. A dynamic adjustment algorithm is designed that can adjust the parameters of the filter based on the characteristics of the interference signal (such as frequency and amplitude) monitored in real time. For example, a microcontroller or digital signal processor (DSP) can be used to analyze the characteristics of the interference signal in real time and dynamically adjust the center frequency and bandwidth of the filter through a control circuit. The dynamically adjusted filter is verified through experimental means. In the actual environment, the interference signal is monitored in real time, and the dynamic adjustment process and suppression effect of the filter are recorded. During the verification process, the suppression effect of the filter (such as suppression depth, response time) and the impact on the useful signal (such as signal distortion, delay, etc.) are evaluated. Ensure that the filter can effectively suppress the interference signal during the dynamic adjustment process without significantly affecting the useful signal.

[0050] In an alternative implementation of this embodiment, the interference mode of electromagnetic interference is predicted according to the matching network parameters of the impedance matching network; a control strategy for suppressing interference is generated according to the interference signal characteristics and the interference mode; the matching network parameters and the filter parameters are adjusted through the control strategy to achieve real-time suppression of the interference signal.

[0051] Specifically, in this embodiment, when predicting the interference mode, potential interference sources and paths can be identified by analyzing the matching network parameters. The variation of the matching network parameters at different frequencies affects the impedance characteristics and electromagnetic compatibility (EMC) of the system. By performing frequency-domain and time-domain analyses on the matching network using electromagnetic simulation software, its impedance characteristics, transmission characteristics, and radiation characteristics within the operating frequency band can be obtained. Based on these data, possible interference frequency bands and interference modes can be identified. For example, in the frequency-domain analysis, it can be observed that the impedance mismatch is relatively severe in certain frequency bands, and these frequency bands may generate stronger reflected signals, resulting in radiation interference. In the time-domain analysis, the rise time and fall time of the signal can be observed, and these timing characteristics affect the intensity and spectral distribution of conducted interference. The characteristics of the interference signal include the location of the interference source, the frequency and amplitude of the interference signal, etc., and these characteristics can be obtained through experimental measurements or simulation analyses. The interference mode is a description of the propagation path and influence range of the interference signal in the system. By combining the interference signal characteristics and the interference mode, targeted control strategies can be formulated to suppress interference. Commonly used interference suppression methods include filtering, shielding, and grounding, etc. In terms of filtering, band-stop filters, low-pass filters, etc. can be designed to attenuate interference signals in specific frequency bands. For example, if the interference signal is concentrated in a certain frequency band, a band-stop filter can be added to the matching network to attenuate the signal in this frequency band to the lowest level to reduce the interference effect. The adjustment of the matching network parameters can be achieved through electrically tunable elements (such as variable capacitors, variable inductors, etc.), and the adjustment of the filter parameters can be achieved through tunable filters. Real-time suppression of interference signals requires the use of adaptive control algorithms, such as adaptive filtering, feedback control, etc. In practical applications, the dynamic adjustment of the matching network parameters and filter parameters is achieved through electrically tunable elements and tunable filters. An adaptive filtering algorithm is adopted to automatically adjust the center frequency and bandwidth of the band-stop filter according to the intensity and frequency of the interference signal monitored in real time, so that it accurately covers the 2.45 GHz frequency band and attenuates the interference signal in this frequency band to the lowest level. At the same time, the capacitance and inductance values of the matching network are adjusted through feedback control to ensure the impedance matching performance of the system within the entire operating frequency band and reduce the generation of reflected signals.

[0052] It should be noted that, in order to better predict the interference mode of electromagnetic interference, this embodiment designs a comprehensive formula to calculate the interference sensitivity of the system, which combines factors such as impedance matching, frequency characteristics, and interference energy distribution. The formula is as follows: , Wherein, is the interference sensitivity at frequency f , is the impedance of the load at frequency f , Denoted as the interference energy factor, it is the energy spectral density of the interference signal at frequency f. is an attenuation coefficient, representing the energy attenuation of high-frequency components. is the input impedance of the matching network at frequency f and is defined as: , where is the imaginary unit, R is the resistance, C is the capacitance, and L is the inductance. Denoted as the impedance mismatch factor, denoted as the high-frequency attenuation factor.

[0053] The impedance mismatch factor describes the degree of impedance mismatch between the matching network and the load. Impedance mismatch will cause an increase in reflected signals, thereby increasing interference. When and are perfectly matched, the factor is 0; when completely mismatched, the factor is 1. The interference energy factor represents the energy density of the interference signal at a specific frequency f and is a direct characteristic of the interference signal. The greater the energy density, the stronger the interference. The high-frequency attenuation factor is used to describe the energy attenuation characteristics of high-frequency signals and can usually be determined through experiments or empirical data.

[0054] It should be noted that impedance mismatch is an important part of interference sensitivity, which reflects the impedance matching degree between the matching network and the load. Impedance mismatch will cause signal reflection and increase the radiation and conduction interference of the system. Therefore, impedance mismatch can directly affect the interference mode. For example, in the high-frequency band, if there is a large impedance mismatch between the matching network and the load, the reflected signal will be enhanced, resulting in an increase in radiation interference. By analyzing impedance mismatch, the interference mode of the system can be identified and predicted. The energy distribution of the interference signal is another important part of interference sensitivity. The energy distributions of interference signals at different frequencies are different, and the interference modes of the system are also different. For example, a large energy distribution of high-frequency interference signals will cause an increase in radiation interference; a large energy distribution of low-frequency interference signals will cause an increase in conduction interference. By analyzing the energy distribution of the interference signal, the frequency characteristics and influence range of the interference mode can be identified. The attenuation characteristics of the high-frequency attenuation factor determine the propagation distance and influence range of the interference signal in the high-frequency band. The greater the high-frequency attenuation, the shorter the propagation distance and the smaller the influence range of the interference signal in the high-frequency band. Therefore, the high-frequency attenuation characteristics can help identify and predict high-frequency interference modes.

[0055] In an optional implementation manner of this embodiment, the method further includes: detecting the interference suppression effect of the control strategy; analyzing the difference in suppression effect by comparing the interference suppression effect with historical interference data; and adjusting the filter parameters and matching network parameters according to the difference in suppression effect.

[0056] Specifically, in this embodiment, the methods for detecting the interference suppression effect include, but are not limited to, using instruments such as spectrum analyzers and network analyzers for measurement. A spectrum analyzer can measure the spectral distribution of signals, identify the frequencies and intensities of interference signals, and a network analyzer can measure the S-parameters (scattering parameters) of the system, including reflection coefficients, transmission coefficients, etc., to evaluate the impedance matching situation and transmission performance of the system. During the detection process, the measured data is compared with the data before the implementation of the control strategy. If the intensity of the interference signal is significantly reduced and the transmission performance of the system is significantly improved, it indicates that the control strategy has achieved good results. Otherwise, the control strategy and parameter configuration need to be further optimized. By comparing the interference suppression effect with historical interference data, the difference in the suppression effect is analyzed. Historical interference data refers to the interference signal data measured at different times and in different environments, and these data can be used as a comparison benchmark to help analyze the effect of the current suppression strategy. By establishing an interference signal database and recording information such as the frequencies, intensities, and interference modes of different interference sources, a comprehensive understanding of the system's performance in various interference environments can be obtained. Comparing the current measured data with the historical data can identify the difference in the suppression effect. For example, if the interference signal in a certain frequency band has been strong in past measurements but is significantly weakened in the current measurement, it indicates that the current suppression strategy has achieved good results in this frequency band. According to the difference in the suppression effect, an adaptive optimization algorithm, such as a genetic algorithm or a particle swarm optimization algorithm, is used to automatically adjust the parameters of the filter and the matching network to achieve the optimal interference suppression effect.

[0057] An electromagnetic interference suppression method for an efficient connector provided by the solution of the present application determines the electromagnetic field distribution data of the efficient connector according to the simulation model of the efficient connector; determines the material property parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis; generates a shielding structure for the efficient connector according to the electromagnetic field distribution data and the material property parameters; determines the impedance characteristic parameters of the efficient connector according to the geometric parameters and the material property parameters of the shielding structure; detects the interference signal characteristics of the interference signal according to the impedance characteristic parameters; and dynamically adjusts the filter parameters through the interference signal characteristics to suppress the interference signal. By implementing the solution of the present application, the interference signal characteristics are accurately detected using the impedance characteristic parameters, and the filter parameters are dynamically adjusted through the interference signal characteristics to suppress the interference signal, improving the accuracy and efficiency of electromagnetic interference suppression.

[0058] Figure 2 An electromagnetic interference suppression device for an efficient connector provided by an embodiment of the present application can be used to implement the electromagnetic interference suppression method for the efficient connector in the foregoing embodiment. As Figure 2 shown, the electromagnetic interference suppression device for the efficient connector mainly includes: The first determination module 10 is configured to determine the electromagnetic field distribution data of the high-efficiency connector according to the simulation model of the high-efficiency connector; The second determination module 20 is configured to determine the material property parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis; The generation module 30 is configured to generate a shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material property parameters; The third determination module 40 is configured to determine the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material property parameters; The detection module 50 is configured to detect the interference signal characteristics of the interference signal according to the impedance characteristic parameters; The control module 60 is configured to dynamically adjust the filter parameters through the interference signal characteristics to suppress the interference signal.

[0059] In an optional implementation manner of this embodiment, the first determination module is specifically configured to: model the geometric structure of the high-efficiency connector to generate a simulation model of the high-efficiency connector; determine the electromagnetic interference prone area corresponding to the high-efficiency connector in the simulation model; determine the electromagnetic field distribution data of the electromagnetic interference prone area through frequency domain scanning.

[0060] In an optional implementation manner of this embodiment, the second determination module is specifically configured to: construct a material microstructure numerical model according to the electromagnetic field strength and energy distribution data; perform electromagnetic performance simulation on the material microstructure numerical model through multi-physics field coupling analysis; simulate the random distribution characteristics of material parameters by the Monte Carlo method; determine the material property parameters of the composite material according to the simulation results of the electromagnetic performance simulation and the random distribution characteristics.

[0061] In an optional implementation manner of this embodiment, the electromagnetic interference suppression device further includes: an optimization module. The optimization module is configured to: determine the shielding effectiveness of the shielding structure; obtain the thermal effect data of the shielding structure during high-frequency signal transmission; optimize the shielding structure according to the shielding effectiveness and the thermal effect data.

[0062] In an optional implementation manner of this embodiment, the third determination module is specifically configured to: generate an impedance matching network according to the impedance characteristic parameters; optimize the impedance characteristic parameters at different signal transmission frequencies in the impedance matching network through an intelligent matching algorithm; optimize the impedance matching network according to the optimized impedance characteristic parameters and the thermal effect data.

[0063] In an optional implementation manner of this embodiment, the control module is further configured to: predict the interference mode of electromagnetic interference according to the matching network parameters of the impedance matching network; generate a control strategy for suppressing interference according to the interference signal characteristics and the interference mode; adjust the matching network parameters and the filter parameters through the control strategy to perform real-time suppression of the interference signal.

[0064] In an optional implementation manner of this embodiment, the control module is further configured to: detect the interference suppression effect of the control strategy; analyze the difference in the suppression effect by comparing the interference suppression effect with historical interference data; adjust the filter parameters and the matching network parameters according to the difference in the suppression effect.

[0065] An electromagnetic interference suppression device for a high-efficiency connector provided by the solution of the present application determines the electromagnetic field distribution data of the high-efficiency connector according to the simulation model of the high-efficiency connector; determines the material property parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis; generates a shielding structure for the high-efficiency connector according to the electromagnetic field distribution data and the material property parameters; determines the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters and the material property parameters of the shielding structure; detects the interference signal characteristics of the interference signal according to the impedance characteristic parameters; dynamically adjusts the filter parameters through the interference signal characteristics to perform interference suppression on the interference signal. Through the implementation of the solution of the present application, the interference signal characteristics are accurately detected by using the impedance characteristic parameters, and the filter parameters are dynamically adjusted through the interference signal characteristics to perform interference suppression on the interference signal, improving the accuracy and efficiency of electromagnetic interference suppression.

[0066] According to the solution provided by the present application Figure 3 An electronic device provided for an embodiment of the present application. This electronic device can be used to implement the electromagnetic interference suppression method for the high-efficiency connector in the foregoing embodiment, and mainly includes: A memory 301, a processor 302, and a computer program 303 stored on the memory 301 and executable on the processor 302. The memory 301 and the processor 302 are communicatively connected. When the processor 302 executes the computer program 303, the electromagnetic interference suppression method for the high-efficiency connector in the foregoing embodiment is implemented. Among them, the number of processors can be one or more.

[0067] The memory 301 can be a high-speed random access memory (RAM, Random Access Memory) or a non-volatile memory, such as a disk memory. The memory 301 is used to store executable program codes, and the processor 302 is coupled to the memory 301.

[0068] Further, the embodiment of the present application also provides a computer-readable storage medium, which can be disposed in the electronic device in the above embodiments, and the computer-readable storage medium can be the memory in the foregoing Figure 3 embodiment shown.

[0069] A computer program is stored on the computer-readable storage medium, and when the program is executed by a processor, it implements the electromagnetic interference suppression method of the high-efficiency connector in the foregoing embodiments. Further, the computer-readable storage medium can also be various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a RAM, a magnetic disk, or an optical disc that can store program codes.

[0070] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0071] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc that can store program codes.

[0072] The above is the description. The above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for suppressing electromagnetic interference of an efficient connector, characterized in that: include: Determining electromagnetic field distribution data of the high-efficiency connector according to a simulation model of the high-efficiency connector; Determine the material characteristic parameters of the composite material under the electromagnetic field distribution data through multi-physics field coupling analysis; Generate a shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material characteristic parameters; Determining impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material characteristic parameters; Detecting interference signal characteristics of the interference signal according to the impedance characteristic parameter; The filter parameters are dynamically adjusted according to the interference signal characteristics to suppress the interference of the interference signal.

2. The electromagnetic interference suppression method of a high-efficiency connector according to claim 1, characterized in that: The step of determining the electromagnetic field distribution data of the high-efficiency connector according to the simulation model of the high-efficiency connector comprises: Modeling the geometric structure of the high-efficiency connector to generate a simulation model of the high-efficiency connector; Determining in the simulation model an area where electromagnetic interference is prone to occur corresponding to the high-efficiency connector; The electromagnetic field distribution data of the area where electromagnetic interference is prone to occur is determined by frequency domain scanning.

3. The electromagnetic interference suppression method of a high-efficiency connector according to claim 1, characterized in that: The electromagnetic field distribution data includes electromagnetic field intensity and energy distribution data, and the step of determining the material characteristic parameters of the composite material under the electromagnetic field distribution data through multi-physical field coupling analysis includes: Constructing a material microstructure numerical model according to the electromagnetic field intensity and the energy distribution data; Simulating electromagnetic performance of the material microstructure numerical model through multi-physics field coupling analysis; Simulate the random distribution characteristics of material parameters through Monte Carlo method; The material characteristic parameters of the composite material are determined according to the simulation results of the electromagnetic performance simulation and the random distribution characteristics.

4. The electromagnetic interference suppression method of a high-efficiency connector according to claim 1, characterized in that: After the step of generating the shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material characteristic parameters, the method further includes: determining the shielding effectiveness of the shielding structure; Acquiring thermal effect data of the shielding structure during high-frequency signal transmission; The shielding structure is optimized according to the shielding effectiveness and the thermal effect data.

5. The electromagnetic interference suppression method of a high-efficiency connector according to claim 4, characterized in that: The step of determining the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material characteristic parameters comprises: Generate an impedance matching network according to the impedance characteristic parameters; In the impedance matching network, the impedance characteristic parameters at different signal transmission frequencies are optimized by an intelligent matching algorithm; The impedance matching network is optimized according to the optimized impedance characteristic parameters and the thermal effect data.

6. The method for suppressing electromagnetic interference of a high-efficiency connector according to claim 5, characterized in that: The method further comprises: predicting an interference pattern of electromagnetic interference according to matching network parameters of the impedance matching network; Generate a control strategy for suppressing interference according to the interference signal characteristics and the interference pattern; The interference signal is suppressed in real time by adjusting the matching network parameters and the filter parameters through the control strategy.

7. The method for suppressing electromagnetic interference of a high-efficiency connector according to claim 6, characterized in that: The method further comprises: detecting the interference suppression effect of the control strategy; By comparing the interference suppression effect with historical interference data, analyzing the difference in suppression effect; The filter parameters and the matching network parameters are adjusted according to the suppression effect difference.

8. An electromagnetic interference suppression device for an efficient connector, characterized in that: The electromagnetic interference suppression device of the high-efficiency connector comprises: A first determination module, configured to determine electromagnetic field distribution data of the high-efficiency connector according to a simulation model of the high-efficiency connector; A second determination module is used to determine the material characteristic parameters of the composite material under the electromagnetic field distribution data through multi-physical field coupling analysis; A generating module, used for generating a shielding structure of the high-efficiency connector according to the electromagnetic field distribution data and the material characteristic parameters; A third determination module, configured to determine the impedance characteristic parameters of the high-efficiency connector according to the geometric parameters of the shielding structure and the material characteristic parameters; A detection module, used to detect interference signal characteristics of the interference signal according to the impedance characteristic parameters; The control module is used to dynamically adjust the filter parameters according to the interference signal characteristics to suppress the interference of the interference signal.

9. An electronic device, characterized in that: The device comprises a memory and a processor, wherein: The processor is used to execute the computer program stored in the memory; When the processor executes the computer program, the steps of the electromagnetic interference suppression method for a high-efficiency connector described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the electromagnetic interference suppression method for a high-efficiency connector described in any one of claims 1 to 7 are implemented.

Images