Modeling method of current injection device for aircraft system-level electromagnetic environment adaptability evaluation

Abstract

The application relates to a current injection device modeling method for evaluating electromagnetic environment adaptability of an aircraft system, comprising the following steps: step one, establishing a structure model of the current injection device; step two, establishing a calibration device matched with the current injection device; step three, presetting a target transmission ratio required by a combined system of the current injection device and the calibration device in a target frequency band; step four, extracting high-frequency parasitic parameters of the current injection device; step five, establishing an equivalent circuit model of the current injection device by inputting the high-frequency parasitic parameters, and deducing an analytical control equation among an input frequency, a magnetic core complex permeability and the transmission ratio; step six, constructing a physical guide deep neural network by taking the frequency as input, the magnetic core complex permeability as output and embedding the analytical control equation; step seven, inversely calculating the magnetic core complex permeability in a wide frequency range by using the physical guide deep neural network; and step eight, assigning the magnetic core complex permeability curve characteristics to the magnetic core of the current injection device.

Description

Technical Field

[0001] This application belongs to the field of simulation and evaluation technology of electromagnetic environment adaptability at the aircraft system level, and specifically relates to a modeling method for a current injection device for electromagnetic environment adaptability evaluation at the aircraft system level. Background Technology

[0002] Aircraft are highly integrated and complex systems, and their safety depends heavily on the proper functioning of various sensitive avionics systems. However, aircraft face extremely harsh electromagnetic environments during service, including internal interference from high-power onboard radio frequency equipment and external interference from lightning, high-intensity radiation fields, and other sources. The resulting electromagnetic energy can intrude into the system through multiple coupling pathways, potentially causing avionics malfunctions and seriously endangering flight safety. Therefore, aircraft system-level electromagnetic environment adaptability assessment is crucial for ensuring flight safety and airworthiness certification.

[0003] Currently, the electromagnetic environment adaptability assessment of aircraft systems relies on test results as the core basis, and repeated iterative optimization based on these results has significant problems such as high cost and long cycle. Using electromagnetic simulation to conduct pre-assessment can effectively reduce the need for subsequent tests.

[0004] Currently, aircraft system-level electromagnetic simulation primarily assesses electromagnetic environment adaptability through direct injection of lightning signals into the aircraft body and plane wave irradiation. While this method can accurately evaluate the overall electromagnetic environment adaptability of different areas on board, it suffers from significant bias in assessing the electromagnetic environment adaptability of local cables due to the difficulty in fully replicating all the detailed features of the aircraft structure in simulation models. Against this backdrop, controlled excitation of cables using current injection devices has become an important engineering approach for assessing the electromagnetic environment adaptability of critical cables.

[0005] The effectiveness of controlled excitation of cables by current injection devices largely depends on the accuracy of the current injection device model. However, existing current injection device models have significant shortcomings in characterizing electromagnetic properties. On the one hand, current injection device models are often simplified to ideal transformers, ignoring parasitic parameters generated by connectors and windings, as well as the nonlinear frequency-varying characteristics of magnetic core materials. On the other hand, the transmission ratio in the simulation model is often affected by the structure and material properties of the current injection device itself, and the transmission ratio changes with frequency.

[0006] Therefore, the electromagnetic environment adaptability assessment of aircraft systems urgently requires a high-precision modeling method for current injection devices that can accurately characterize wideband characteristics, adapt to different mission requirements, and whose transmission ratio can be arbitrarily set to a constant value, in order to reduce reliance on experiments and significantly reduce R&D costs and time.

[0007] In view of the above, this application is hereby filed. Summary of the Invention

[0008] The purpose of this application is to provide a current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment, which can inject a quantitative interference coupling current into the cable based on the current injection device, assess the system's tolerance to electromagnetic interference, and improve the efficiency and capability of aircraft system-level electromagnetic immunity assessment.

[0009] The technical solution of this application is:

[0010] A method for modeling current injection devices for aircraft system-level electromagnetic environment adaptability assessment, comprising:

[0011] Step 1: Establish the structural model of the current injection device;

[0012] Step 2: Establish a calibration device to be used with the current injection device;

[0013] Step 3: Preset the target transmission ratio that the current injection device and calibration device combination system needs to achieve within the target frequency band;

[0014] Step 4: Extract the high-frequency parasitic parameters of the current injection device;

[0015] Step 5: Substitute high-frequency parasitic parameters to establish an equivalent circuit model of the current injection device, and derive the analytical control equations between the input frequency, the complex permeability of the magnetic core, and the transmission ratio.

[0016] Step 6: Using frequency as input and the complex permeability of the magnetic core as output, embed analytical control equations as constraints to construct a physically guided deep neural network;

[0017] Step 7: Using a physically guided deep neural network, the complex permeability of the magnetic core at each frequency point is inverted over a wide frequency range to derive the complex permeability curve of the magnetic core.

[0018] Step 8: Apply the complex permeability curve characteristics of the magnetic core to the magnetic core of the current injection device.

[0019] According to at least one embodiment of this application, the above-described modeling method for current injection devices in aircraft system-level electromagnetic environment adaptability assessment further includes:

[0020] Step 9: Simulate and solve the combined system of current injection device and calibration device to calculate the transmission ratio across the entire frequency band and verify its flatness over a wide bandwidth.

[0021] According to at least one embodiment of this application, in the above-described modeling method for current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step one, the initial geometric configuration, spatial dimensions, and basic configuration parameters of the current injection device are determined based on the frequency range, injection current intensity, and installation space limitations of the aircraft system-level electromagnetic environment adaptability assessment simulation.

[0022] The curved surface structure of the current injection device is modified into a regular cubic structure.

[0023] According to at least one embodiment of this application, in the above-described modeling method for the current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step two, the calibration device is a coaxial structure with flexibly adjustable dimensions, capable of freely adjusting typical characteristic impedances of 50Ω and 75Ω.

[0024] According to at least one embodiment of this application, in the above-described modeling method for the current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step three, based on the interference current that is expected to be injected into the cable in the simulation of aircraft system-level electromagnetic environment adaptability assessment, a target transmission ratio that the current injection device and calibration device combination system needs to achieve in the target frequency band is preset, and the target curve is set as an ideal response with constant amplitude and fluctuation of less than 1dB.

[0025] According to at least one embodiment of this application, in the above-described modeling method for current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step four, a three-dimensional full-wave electromagnetic model of the current injection device is established using ANSYS Q3D, and the high-frequency parasitic parameters of the current injection device, including distributed capacitance, distributed inductance, and shell equivalent impedance, are obtained through simulation.

[0026] According to at least one embodiment of this application, in the above-described modeling method for the current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step five, based on the law of electromagnetic induction and transmission line theory, high-frequency parasitic parameters are introduced to establish an equivalent circuit model of the current injection device, and analytical control equations regarding frequency, magnetic core permeability, and transmission ratio are derived.

[0027] According to at least one embodiment of this application, in the above-described modeling method for the current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step six, a loss function is constructed for the difference between the current transmission ratio and the target transmission ratio.

[0028] According to at least one embodiment of this application, in the above-described modeling method for current injection devices for aircraft system-level electromagnetic environment adaptability assessment, in step eight, the set of complex permeability curves of the magnetic core is imported into the material property library of the electromagnetic simulation software in the form of a list, and assigned to the magnetic core of the current injection device.

[0029] According to at least one embodiment of this application, in the above-described modeling method for the current injection device for aircraft system-level electromagnetic environment adaptability assessment, in step nine, if the calculated transmission ratio fluctuates at a specific frequency point, the deviation characteristics are fed back to the physical-guided deep neural network for local weight adjustment and secondary iterative optimization. Attached Figure Description

[0030] Figure 1 This is a flowchart of the current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment provided in this application embodiment;

[0031] Figure 2 This is a schematic diagram of the current injection device provided in the embodiments of this application;

[0032] Figure 3 This is a schematic diagram of a constant transmission ratio curve provided in an embodiment of this application.

[0033] To better illustrate this embodiment, some content in the accompanying drawings may be omitted, enlarged, or reduced. They are for illustrative purposes only and should not be construed as limiting the scope of this application. Detailed Implementation

[0034] To make the technical solution and advantages of this application clearer, the technical solution of this application will be described in a clearer and more complete manner below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only some embodiments of this application, and are only used to explain this application, not to limit this application. It should be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, and other related parts can be referred to the general design.

[0035] Furthermore, unless otherwise defined, the technical or scientific terms used in this application description shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The word "comprising" as used in this application description indicates that the concept preceding the word encompasses the concepts listed following the word and their equivalents, without excluding other related concepts.

[0036] A modeling method for current injection devices in aircraft system-level electromagnetic environment adaptability assessment, such as... Figure 1 As shown.

[0037] Preliminary preparations and target setting: optimization of current injection device configuration and establishment of constant gain target.

[0038] Step 1: Establish the structural model of the current injection device.

[0039] Based on the frequency range, injected current intensity, and installation space limitations of the aircraft system-level electromagnetic environment adaptability assessment simulation, the initial geometric configuration, spatial dimensions, and basic configuration parameters of the current injection device are determined.

[0040] To improve mesh generation efficiency and convergence accuracy in computational electromagnetics, the curved surface structure of the current injection device is modified into a regular cubic structure, which facilitates mesh generation, ensures high-quality elements in finite element analysis, and improves simulation efficiency.

[0041] Step 2: Establish a calibration device that is compatible with the current injection device.

[0042] The calibration device is a coaxial structure with adjustable dimensions, which can freely adjust typical characteristic impedances such as 50Ω and 75Ω.

[0043] Step 3: Set the target transmission ratio (TPR) to be achieved within the target frequency band by presetting the current injection device and calibration device combination system.

[0044] Based on the simulation of electromagnetic environment adaptability assessment of aircraft system, the interference current to be injected into the cable is preset. The current injection device and calibration device combination system are pre-set. The target transmission ratio to be achieved in the target frequency band is set as the ideal response with constant amplitude and fluctuation of less than 1dB, which is used as the optimization target of the entire modeling process.

[0045] Core Modeling and Parameter Inversion: Solving for the Characteristics of Smart Magnetic Cores Based on Physical Constraints.

[0046] Step 4: Extract the high-frequency parasitic parameters of the current injection device.

[0047] Using ANSYS Q3D, a three-dimensional full-wave electromagnetic model of the current injection device was established, and high-frequency parasitic parameters such as distributed capacitance, inductance, and equivalent resistance of the housing between the connector, coil winding, and housing were obtained through simulation.

[0048] Step 5: Substitute high-frequency parasitic parameters to establish an equivalent circuit model of the current injection device, and derive the analytical control equations between the input frequency, the complex permeability of the magnetic core, and the transmission ratio.

[0049] Based on the law of electromagnetic induction and transmission line theory, and by incorporating high-frequency parasitic parameters, an equivalent circuit model of the current injection device is established, and analytical control equations relating frequency, core permeability, and transmission ratio are derived.

[0050] Step 6: Using frequency as input and the complex permeability of the magnetic core as output, embed analytical control equations as constraints to construct a physically guided deep neural network.

[0051] Construct a loss function for the difference between the current transmission ratio and the target transmission ratio.

[0052] Step 7: Using a physical-guided deep neural network, the complex permeability of the magnetic core at each frequency point is inverted within a wide frequency range, and the complex permeability curve of the magnetic core is derived, that is, the ideal frequency-varying magnetic core complex permeability curve that can achieve constant gain is intelligently inverted.

[0053] Step 8: Apply the complex permeability curve characteristics of the magnetic core to the magnetic core of the current injection device.

[0054] The set of complex permeability curves of the magnetic core is imported into the material property library of the electromagnetic simulation software in the form of a list, and then assigned to the magnetic core of the current injection device.

[0055] Verification of iterations and model output: Simulation implementation and verification of wideband constant gain characteristics.

[0056] Step 9: Simulate and solve the combined system of current injection device and calibration device to calculate the transmission ratio across the entire frequency band and verify its flatness over a wide bandwidth.

[0057] If the calculated transmission ratio fluctuates at a specific frequency, the deviation characteristics are fed back to the physical-guided deep neural network for local weight adjustment and secondary iterative optimization.

[0058] After determining the model to be valid, an ideal current injection device model with wideband constant gain characteristics is output.

[0059] In a specific example, the electromagnetic environment adaptability assessment object is the cable of an aircraft communication system. A virtual electromagnetic immunity test is performed on it in the 100kHz to 600MHz frequency band, requiring the injection of an interference current of 100mA. An ideal current injection device model with a constant transmission ratio of -10dB is constructed. The aforementioned modeling method for the current injection device in the aircraft system-level electromagnetic environment adaptability assessment is implemented as follows:

[0060] 1. Based on the space constraints within the equipment compartment, the current injection device is determined to be a cubic structure with a maximum outer envelope size of 100mm, made of aluminum alloy. The magnetic core and windings of the current injection device are also set to be cubic structures, and N-type connectors are used. A structural model of the current injection device is established.

[0061] In the 3D electromagnetic software CST, all curved surface structures in the current injection device are optimized into regular cubic structures, such as... Figure 2 As shown.

[0062] 2. The matching calibration device is designed with a coaxial air wire structure. The conductor diameter can be continuously adjusted from 1.0mm to 4.0mm, and the inner diameter of the outer conductor can be varied from 4.5mm to 13.0mm, so as to achieve the setting of characteristic impedance from 45Ω to 150Ω.

[0063] 3. The target transmission ratio S21 of the preset current injection device and calibration device system is -10dB in the full frequency band from 100kHz to 600MHz, and the allowable fluctuation tolerance is ±1dB.

[0064] 4. In ANSYS Q3D, import the 3D model of the current injection device into the electromagnetic simulation software, and extract high-frequency parasitic parameters such as the distributed capacitance, distributed inductance, and equivalent impedance of the shell through simulation.

[0065] 5. Based on high-frequency parasitic parameters and electromagnetic induction laws and other related electromagnetic theories, an equivalent circuit including the number of winding turns, winding distributed inductance, and winding distributed capacitance is established. On this basis, analytical control equations concerning the relationship between input frequency f, core permeability μ, and output transmission ratio S21 are derived.

[0066] 6. Construct a physically guided deep neural network with 4 hidden layers and 64 neurons in each layer. The input frequency f is the input layer, and the complex permeability μ of the magnetic core corresponding to each frequency point is the output layer. The analytical control equations are the physical constraints.

[0067] Constructing a composite loss function ,in, For data loss function, , The physical loss function is to substitute the complex permeability μ of the magnetic core output by the physical-guided deep neural network into the analytical control equation to calculate the physical deviation.

[0068] 7. Using a physically guided deep neural network, the optimal magnetic core complex permeability μ is inverted point by point within the range of 100kHz-600MHz at 1MHz intervals.

[0069] 8. Import the inverted magnetic core complex permeability μ dataset into the CST material library of the three-dimensional electromagnetic software, and assign this material property to the magnetic core structure of the current injection device.

[0070] 9. Perform frequency scanning calculations within the range of 100kHz to 600MHz, calculate the transmission ratio S21 for each frequency, and the optimized transmission ratio S21 curve is shown below. Figure 3 As shown.

[0071] After the model is verified, an ideal current injection device model with constant gain characteristics is output and placed in an aircraft system-level simulation scenario.

[0072] The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment disclosed in the above embodiments, by embedding the physical circuit model into a neural network, inversely derives the ideal magnetic core characteristics for compensating parasitic parameters, and realizes wideband constant gain controllable modeling, which can provide a powerful digital analysis tool for aircraft electromagnetic safety design.

[0073] The technical solution of this application has been described in conjunction with the preferred embodiments shown in the accompanying drawings. Those skilled in the art should understand that the protection scope of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of this application.

Claims

1. A method for modeling a current injection device for evaluating the electromagnetic environment adaptability of an aircraft system, characterized in that, include: Step 1: Establish the structural model of the current injection device; Step 2: Establish a calibration device to be used with the current injection device; Step 3: Preset the target transmission ratio that the current injection device and calibration device combination system needs to achieve within the target frequency band; Step 4: Extract the high-frequency parasitic parameters of the current injection device; Step 5: Substitute high-frequency parasitic parameters to establish an equivalent circuit model of the current injection device, and derive the analytical control equations between the input frequency, the complex permeability of the magnetic core, and the transmission ratio. Step 6: Using frequency as input and the complex permeability of the magnetic core as output, embed analytical control equations as constraints to construct a physically guided deep neural network; Step 7: Using a physically guided deep neural network, the complex permeability of the magnetic core at each frequency point is inverted over a wide frequency range to derive the complex permeability curve of the magnetic core. Step 8: Apply the complex permeability curve characteristics of the magnetic core to the magnetic core of the current injection device.

2. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 1, characterized in that, Also includes: Step 9: Simulate and solve the combined system of current injection device and calibration device to calculate the transmission ratio across the entire frequency band and verify its flatness over a wide bandwidth.

3. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 2, characterized in that, In step one, based on the frequency range, injected current intensity, and installation space limitations of the aircraft system-level electromagnetic environment adaptability assessment simulation, the initial geometric configuration, spatial dimensions, and basic configuration parameters of the current injection device are determined. The curved surface structure of the current injection device is modified into a regular cubic structure.

4. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 3, characterized in that, In step two, the calibration device is a coaxial structure with adjustable dimensions, which can freely adjust the typical characteristic impedance of 50Ω and 75Ω.

5. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 4, characterized in that, In step three, based on the aircraft system-level electromagnetic environment adaptability assessment simulation, the interference current to be injected into the cable is preset, and the current injection device and calibration device combination system is preset. The target transmission ratio to be achieved in the target frequency band is set as an ideal response with constant amplitude and fluctuation of less than 1dB.

6. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 5, characterized in that, In step four, a three-dimensional full-wave electromagnetic model of the current injection device is established using ANSYS Q3D, and the high-frequency parasitic parameters of the current injection device, including distributed capacitance, distributed inductance and shell equivalent impedance, are obtained through simulation.

7. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 6, characterized in that, In step five, based on the law of electromagnetic induction and transmission line theory, high-frequency parasitic parameters are introduced to establish an equivalent circuit model of the current injection device, and analytical control equations concerning frequency, core permeability, and transmission ratio are derived.

8. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 7, characterized in that, In step six, a loss function is constructed for the difference between the current transmission ratio and the target transmission ratio.

9. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 8, characterized in that, In step eight, the set of complex permeability curves of the magnetic core is imported into the material property library of the electromagnetic simulation software in the form of a list, and then assigned to the magnetic core of the current injection device.

10. The current injection device modeling method for aircraft system-level electromagnetic environment adaptability assessment according to claim 9, characterized in that, In step nine, if the calculated transmission ratio fluctuates at a specific frequency, the deviation characteristics are fed back to the physical-guided deep neural network for local weight adjustment and secondary iterative optimization.

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