A multi-degree-of-freedom specific reflection metamaterial topology design method

Abstract

This invention discloses a method for designing the topology of a multi-degree-of-freedom specific reflective metamaterial, relating to the field of microwave wireless power transmission technology. The method includes dividing the target region of a single metamaterial into multiple sub-grids, encoding these sub-grids to obtain a grid topology code; constructing an optimization objective function and constraints; initializing the grid topology code to construct an initial population; calculating the electromagnetic response characteristics of individuals in the initial population; and then constructing the topology based on the optimization objective function, the constraints, and the electromagnetic response characteristics. This invention, by discretizing and encoding the target region of a single metamaterial into sub-grids, constructing an optimization objective function and constraints, and combining iterative optimization to obtain the optimal grid topology code, and then constructing the metamaterial topology, can improve the topology design flexibility and beam control adaptability of metamaterials, optimize the energy reflection distribution, and improve reflection performance during wireless power transmission.

Description

Technical Field

[0001] This invention relates to the field of microwave wireless power transmission technology, and in particular to a method for designing a topological structure of a multi-degree-of-freedom special reflective metamaterial. Background Technology

[0002] Microwave wireless power transfer technology can transfer electrical energy in space without contact, and has wide application needs in scenarios such as mobile devices, IoT terminals, and drones. In actual transmission environments, it is often difficult to keep the transmitter and receiver coaxial, and the transmission path is easily blocked by obstacles. It is necessary to use electromagnetic metamaterials to achieve special reflection of electromagnetic waves, so that the beam can propagate along a preset direction and complete energy convergence, providing a feasible solution for efficient wireless power transfer in complex scenarios.

[0003] Traditional special reflective metamaterials mostly adopt metallic dielectric structures. Performance optimization is achieved by adjusting a few geometric parameters such as the width and depth of rectangular slots. Beam control is achieved by adjusting the size of a fixed shape. The related design process relies on manual parameter traversal and experience-based value selection, making it difficult to adapt to diverse transmission angles and operating frequency band requirements.

[0004] Traditional designs rely on only a few geometric variables for optimization, resulting in insufficient freedom of structural parameters. This makes them unsuitable for complex operating conditions such as dual polarization, multiple frequency points, and large-angle incidence. They also struggle to suppress redundant diffraction modes such as specular reflection and parasitic radiation, which reduces the energy transmission efficiency of the target's specific reflection channel. Consequently, they fail to meet the requirements for multi-band, large-angle, and high-efficiency electromagnetic wave redirection and energy convergence. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a multi-degree-of-freedom method for designing topological structures of special reflective metamaterials, which solves the technical problems of low design freedom, limited beam control capability, and low special reflection efficiency in existing technologies.

[0006] The technical means employed in this invention are as follows: This invention provides a method for designing topological structures of multi-degree-of-freedom special reflective metamaterials, including: The target region of the single metamaterial is divided into multiple sub-grids, and the multiple sub-grids are encoded to obtain the grid topology code; Construct the optimization objective function and constraints; The grid topology code is initialized to construct an initial population. The electromagnetic response characteristic values ​​of individuals in the initial population are calculated. Based on the optimization objective function, the constraints, and the electromagnetic response characteristic values, the initial population is iteratively optimized to obtain the optimal grid topology code. The metamaterial topology is constructed based on the optimal mesh topology encoding.

[0007] Furthermore, encoding the multiple sub-grids includes: encoding the multiple sub-grids using a one-dimensional binary array.

[0008] Furthermore, the objective function for optimization is the bistatic radar cross section of the metamaterial array in the target elevation direction.

[0009] Furthermore, the constraints include an optimized stop threshold and upper and lower limits for the scan pitch angle.

[0010] Furthermore, the calculation of the electromagnetic response characteristics of individuals in the initial population includes: calculating the electromagnetic response characteristics of individuals in the initial population using finite element method full-wave simulation software.

[0011] Further, the step of iteratively optimizing the initial population based on the objective function, the constraints, and the electromagnetic response characteristic values ​​to obtain the optimal grid topology encoding includes: Based on the electromagnetic response characteristic values ​​and the optimization objective function, the fitness of individuals in the initial population is calculated; Based on the fitness, crossover and mutation operations are performed on individuals in the initial population to generate a new generation of population; Select the current best individual from the new generation population; Determine whether the grid topology code corresponding to the current optimal individual satisfies the preset convergence condition; If the conditions are not met, the current population will be updated to the new generation population and iterative calculations will be performed. If the conditions are met, the grid topology code corresponding to the current best individual is taken as the optimal grid topology code.

[0012] Furthermore, the preset convergence condition is that the change in the objective function value corresponding to the current best individual is less than a preset threshold, or the number of iterations reaches a preset number.

[0013] Furthermore, the step of constructing the metamaterial topology based on the optimal mesh topology encoding includes: The optimal mesh topology code is analyzed to determine the material distribution and geometric configuration of the metamaterial structural unit; Based on the material distribution and geometric configuration, a corresponding metamaterial topology is constructed.

[0014] Furthermore, the metamaterial topology is a three-layer structure.

[0015] Compared with the prior art, the present invention has the following advantages: This invention discretizes and encodes the target region of a single metamaterial into sub-grids, constructs an optimization objective function and constraints, and obtains the optimal grid topology code through iterative optimization. Based on this, the metamaterial topology structure is constructed, which can improve the topology design flexibility and beam control adaptability of metamaterials, optimize the energy reflection distribution, and improve the reflection performance in the wireless energy transmission process.

[0016] Based on the above reasons, this invention can be widely applied in fields such as microwave wireless power transmission. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a diagram of a traditional single-variable metamaterial structure. Figure 2 This is a schematic diagram of the process of using finite element method full-wave simulation and genetic algorithm optimization in this invention; Figure 3 This is a topological diagram of the metamaterial of this invention; Figure 4 The diagram shows the structure of a three-layer special reflective metamaterial, including (a) a top view of the first layer metal mesh, (b) a top view of the second layer groove array, (c) a top view of the third layer metal patch, and (d) a three-dimensional view of the three-layer special reflective metamaterial. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "comprising" and "having" and any variations thereof in this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0021] Microwave wireless power transfer technology can transfer electrical energy in space without contact, and has wide application needs in scenarios such as mobile devices, IoT terminals, and drones. In actual transmission environments, it is often difficult to keep the transmitter and receiver coaxial, and the transmission path is easily blocked by obstacles. It is necessary to use electromagnetic metamaterials to achieve special reflection of electromagnetic waves, so that the beam can propagate along a preset direction and complete energy convergence, providing a feasible solution for efficient wireless power transfer in complex scenarios.

[0022] Please see Figure 1 , Figure 1 This is a diagram of a traditional single-variable metamaterial structure.

[0023] Traditional special reflective metamaterials mostly adopt metallic dielectric structures. Performance optimization is achieved by adjusting a few geometric parameters such as the width and depth of rectangular slots. Beam control is achieved by adjusting the size of a fixed shape. The related design process relies on manual parameter traversal and experience-based value selection, making it difficult to adapt to diverse transmission angles and operating frequency band requirements.

[0024] Traditional designs rely on only a few geometric variables for optimization, resulting in insufficient freedom of structural parameters. This makes them unsuitable for complex operating conditions such as dual polarization, multiple frequency points, and large-angle incidence. They also struggle to suppress redundant diffraction modes such as specular reflection and parasitic radiation, which reduces the energy transmission efficiency of the target's specific reflection channel. Consequently, they fail to meet the requirements for multi-band, large-angle, and high-efficiency electromagnetic wave redirection and energy convergence.

[0025] The embodiments of the present invention will now be described with reference to the accompanying drawings.

[0026] This invention provides a method for designing topological structures of multi-degree-of-freedom special reflective metamaterials, comprising the following steps: Step 101: Divide the target region of the monolithic metamaterial into multiple sub-grids, and encode these sub-grids to obtain a grid topology code. This encoding method can discretize the target region of the monolithic metamaterial into quantifiable topological units, which facilitates the optimization and adjustment of the material distribution of each sub-grid based on preset constraints to achieve different electromagnetic response characteristics.

[0027] The target region (i.e., the design region) of the monolithic metamaterial is divided into M×N sub-grids, and the size of each sub-grid is set to... By dividing the target area into regular sub-grids, the controllability and operability of the topology design process can be improved.

[0028] In some embodiments, encoding multiple sub-grids includes: encoding multiple sub-grids using a one-dimensional binary array. Here, 0 represents the absence of a metal structure at the grid location, and 1 represents the presence of a high-conductivity metal structure at the grid location. By arranging and combining the binary array in different ways, various complex topological layouts can be expressed, thereby breaking the limitations of traditional fixed shapes and forming different metal groove arrangements.

[0029] Step 102: Construct the optimization objective function and constraints. By clearly defining the optimization objective function and constraints, the topology optimization process of a single metamaterial can be guided in a targeted manner to improve the energy concentration in the specific reflection direction, thus meeting the needs of multi-degree-of-freedom wireless power transmission scenarios.

[0030] In some embodiments, the objective function is optimized. For metamaterial arrays at target elevation angle The bistatic radar cross section in the direction of the target's specific reflection direction; the core design objective of this optimization is to maximize the power in the specific reflection direction of the target. Maximize the proportion of power in the sum of all reflection directions.

[0031] In some embodiments, the constraints include an optimization stop threshold and upper and lower limits for the scan pitch angle; the upper limit of the scan pitch angle is θ. up The lower limit is θ low It can limit the range of scanning elevation angles of metamaterial arrays, so that the optimization process is focused on the target angle range, in order to achieve efficient and unique reflection characteristics at specific elevation angles.

[0032] Step 103: Initialize the mesh topology encoding to construct an initial population. Calculate the electromagnetic response characteristics of individuals in the initial population. Based on the optimization objective function, constraints, and electromagnetic response characteristics, iteratively optimize the initial population to obtain the optimal mesh topology encoding. In the initial population, each individual represents a specific set of metamaterial unit topology arrangement parameters. This process can perform directional optimization of the topology of a single metamaterial under preset constraints, making the metamaterial structure corresponding to the obtained optimal mesh topology encoding more likely to achieve the specific reflection characteristics at the target pitch angle.

[0033] Please see Figure 2 , Figure 2 This is a flowchart illustrating the topological design method for a multi-degree-of-freedom specific reflective metamaterial according to the present invention.

[0034] In some embodiments, calculating the electromagnetic response characteristics of individuals in the initial population includes: calculating the electromagnetic response characteristics of individuals in the initial population using finite element method (FEM) full-wave simulation software. This can effectively evaluate the electromagnetic response of individual metamaterial structures corresponding to different mesh topology codes, providing a reliable performance basis for the iterative optimization process.

[0035] In some embodiments, the initial population is iteratively optimized based on the objective function, constraints, and electromagnetic response characteristics to obtain the optimal grid topology encoding, including the following steps: Step 1031: Calculate the fitness of individuals in the initial population based on electromagnetic response characteristic values ​​and an optimization objective function. Using electromagnetic response characteristic values ​​as a basis, and combining them with an optimization objective function, quantify the matching degree of each grid topology-coded individual to the specific reflection target, facilitating the differentiation of performance across different topologies. Specifically, firstly, each binary-coded chromosome in the initial population is inverted and reconstructed to generate a multi-layered grooved grid topology. In the coding, "1" represents a metal-paved grid region, and "0" represents a blank groove region. Then, the reconstructed supercell model is imported into HFSS to complete full-wave electromagnetic simulation. For a target at 5.8 GHz and 60° oblique incidence, the normalized bistatic RCS at a specific reflection angle of -10° is extracted as the electromagnetic response characteristic value and substituted into the objective function to solve for the fitness. The final output fitness value can intuitively quantify the beam-directed control capability of different grid topologies. A higher value indicates a stronger specific reflection efficiency of the three-layered supercell structure, thus achieving performance differentiation among various metal grooved topologies.

[0036] Step 1032: Based on fitness, crossover and mutation operations are performed on individuals in the initial population to generate a new generation population. Individuals with superior mesh topology coding performance are selected based on fitness. Crossover and mutation operations are used to reorganize and fine-tune the topology structure, improving the global search capability of the metamaterial topology optimization process and reducing the possibility of getting trapped in local optima. A roulette wheel selection strategy is adopted, allocating selection probabilities according to the fitness ratio of each coding individual, prioritizing the retention of three-layer supercell coding with high specific reflection efficiency. The crossover operation randomly extracts two high-quality mesh binary vectors and swaps their segments, completing the global reorganization of multi-layer groove layout and mesh size. The mutation operation randomly flips the binary bits within the coding, performing local fine-tuning of microstructural parameters such as the width and depth of single-layer and multi-layer grooves. The crossover operation broadens the global optimization range of the topology structure, while the mutation operation avoids the local optima defects caused by single dimensions. Together, they fully cover the multi-degree-of-freedom design space of the three-layer metamaterial, ultimately generating a completely new offspring population.

[0037] Step 1033: Select the current best individual from the new generation population. Select the mesh topology-coded individual with the highest fitness from the new generation population. This allows for real-time tracking of the optimization progress of the metamaterial topology, ensuring that the iteration process always revolves around performance improvement. Iterate through the fitness calculation results corresponding to all codes in the new generation population, selecting the binary mesh vector with the largest peak value of the target reflection angle's normalized RCS. Simultaneously cache the complete set of structural parameters for the three-layer metamaterial matched by this code, including the number of rows and columns M and N of each layer's mesh, as well as the length and width dx and dy of the sub-mesh. Compare the scattering curves and specific reflection efficiencies of the current best topology with those of the globally best individuals in historical iterations. If the current structure performs better, update the globally best topology archive. Simulation data of each generation of the best metamaterial is retained throughout the process, allowing for intuitive tracking of the iterative improvement trend of metamaterial beam control performance during iteration.

[0038] Step 1034: Determine whether the mesh topology code corresponding to the current best individual meets the preset convergence condition. If not, update the current population to a new generation population and perform iterative calculations. If it meets the condition, use the mesh topology code corresponding to the current best individual as the optimal mesh topology code. By controlling the timing of iteration termination through preset convergence conditions, the optimization effect of the metamaterial topology can be guaranteed while reasonably controlling the consumption of computational resources, and efficiently obtaining the optimal mesh topology code that meets the requirements of multi-degree-of-freedom specific reflection. A dual convergence criterion is set: first, the fitness improvement of the globally best individual for 15 consecutive generations is less than the preset threshold a = 0.02; second, the number of iterations reaches the maximum iteration limit of 100. Meeting either condition is sufficient to determine optimization convergence. If the convergence criterion is not met, the new generation of offspring replaces the original population, and the process jumps to the fitness calculation stage for the next iteration. If convergence is determined, the optimal binary mesh encoding is reverse-analyzed to solve for the complete set of structural parameters, including the groove arrangement and mesh size of each layer of the three-layer metamaterial, to obtain the optimal supercell topology adapted to the specific operating conditions of 5.8 GHz and 60° incident temperature to -10°, thus ending the overall topology optimization process. In some embodiments, the preset convergence condition is that the change in the objective function value corresponding to the current best individual is less than a preset threshold, or the number of iterations reaches a preset number.

[0039] During the iteration process, when the change in the objective function value corresponding to the current best individual is less than a preset threshold, it indicates that the performance improvement of the metamaterial topology has stabilized and further iteration is unnecessary. When the number of iterations reaches a preset number, the iteration process is terminated regardless of whether the objective function value is stable, thus avoiding unlimited consumption of computational resources. This dual-determination mechanism can flexibly control the termination timing of the metamaterial topology optimization process. It can terminate the iteration in a timely manner when the objective function value tends to stabilize to avoid overcomputation, and it can also force termination within a preset number of iterations to prevent the optimization process from falling into an invalid loop, ensuring a balance between overall optimization efficiency and effectiveness.

[0040] Step 104: Construct the metamaterial topology based on the optimal mesh topology code. The digital code obtained from topology optimization is converted into physically realizable metamaterial structural units to construct the metamaterial topology based on the optimal mesh topology code.

[0041] In some embodiments, constructing a metamaterial topology based on the optimal mesh topology code includes: parsing the optimal mesh topology code to determine the material distribution and geometric configuration of the metamaterial structural units; and constructing the corresponding metamaterial topology based on the material distribution and geometric configuration.

[0042] By analyzing the optimal mesh topology encoding, the material distribution (metal / dielectric) and geometric configuration of each sub-mesh are determined; then, based on the material distribution and geometric configuration, the corresponding metamaterial structural units are processed or prepared, ultimately forming a complete topological structure.

[0043] Please see Figure 3 , Figure 3 This is a topological diagram of the metamaterial of the present invention. The metamaterial topological structure of the present invention is an irregular metal configuration obtained by mesh topological coding optimization. It forms specific grooves and contour structures through the material distribution differences at the sub-mesh level, which can adapt to the preset electromagnetic control requirements and provide a structural basis for achieving efficient and specific reflection.

[0044] Please see Figure 4 , Figure 4 This is a structural diagram of a three-layered special reflective metamaterial.

[0045] In some embodiments, the metamaterial topology is a three-layer structure.

[0046] The metamaterial topology consists of a top metal patch layer, an intermediate dielectric substrate layer, and a bottom metal ground layer. The three layers work together to achieve unique reflective properties.

[0047] Specifically, for microwave wireless power transmission scenarios with an operating frequency of 5.8 GHz and an incident angle of 60°, this embodiment designs a three-layer stacked all-metal special reflective metamaterial structure. The overall width of the metamaterial unit is 74.7 mm, and its dimensions are 74.7 mm × 51.72 mm. The unit height of the first and third layers is set to 6 mm, and the unit height of the second layer is set to 7 mm. Different groove structures of varying depths and shapes are formed between the layers through differences in metal distribution. The reflective material used is copper with high electrical conductivity.

[0048] Regarding the specific three-layer topology mesh parameter settings: the first layer is divided into 13×8 sub-mesh (i.e., M1=13, N1=8), with a corresponding sub-mesh size of d. x1 =6.30mm, d y1=6.64mm; the second layer is divided into 25×18 sub-grids (i.e., M2=25, N2=18), with a corresponding sub-grid size of d. x2 =3.30mm, d y2 =3.44mm; the third layer is divided into 15×10 sub-grids (i.e., M3=15, N3=10), with a corresponding sub-grid size of d. x3 =5.40mm, d y3 =5.35mm. The metal material is distributed strictly according to the optimized "0 / 1" matrix inside each layer. An ideal electrical conductor (PE) boundary condition is set on the outer surface of the optimized reflective unit, and the unit cell is replicated along the horizontal x and y directions and arranged into a 6×4 periodic reflective array.

[0049] Through the above specific embodiment structure, it is possible to achieve beam deflection with strong reflection characteristics and high directionality (such as specific reflection in the -10° direction) for electromagnetic waves incident at a large angle of 60°, effectively suppressing useless specular reflection and parasitic radiation, and significantly improving the directional transmission efficiency of wireless energy.

[0050] This invention discretizes and encodes the target region of a single metamaterial into sub-grids, constructs an optimization objective function and constraints, and obtains the optimal grid topology code through iterative optimization. Based on this, the metamaterial topology structure is constructed, which can improve the topology design flexibility and beam control adaptability of metamaterials, optimize the energy reflection distribution, and improve the reflection performance in the wireless energy transmission process.

[0051] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for designing a multi-degree-of-freedom metamaterial topology with specific reflection, characterized in that, include: The target region of the single metamaterial is divided into multiple sub-grids, and the multiple sub-grids are encoded to obtain the grid topology code; Construct the optimization objective function and constraints; The grid topology code is initialized to construct an initial population. The electromagnetic response characteristic values ​​of individuals in the initial population are calculated. Based on the optimization objective function, the constraints, and the electromagnetic response characteristic values, the initial population is iteratively optimized to obtain the optimal grid topology code. The metamaterial topology is constructed based on the optimal mesh topology encoding.

2. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, Encoding the multiple subgrids includes: encoding the multiple subgrids using a one-dimensional binary array.

3. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, The objective function for optimization is the bistatic radar cross section of the metamaterial array in the target elevation direction.

4. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, The constraints include an optimized stop threshold and upper and lower limits for the scan pitch angle.

5. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, The calculation of the electromagnetic response characteristics of individuals in the initial population includes: calculating the electromagnetic response characteristics of individuals in the initial population using finite element method full-wave simulation software.

6. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, The step of iteratively optimizing the initial population based on the objective function, the constraints, and the electromagnetic response characteristic values ​​to obtain the optimal grid topology encoding includes: Based on the electromagnetic response characteristic values ​​and the optimization objective function, the fitness of individuals in the initial population is calculated; Based on the fitness, crossover and mutation operations are performed on individuals in the initial population to generate a new generation of population; Select the current best individual from the new generation population; Determine whether the grid topology code corresponding to the current optimal individual satisfies the preset convergence condition; If the conditions are not met, the current population will be updated to the new generation population and iterative calculations will be performed. If the conditions are met, the grid topology code corresponding to the current best individual is taken as the optimal grid topology code.

7. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 6, characterized in that, The preset convergence condition is that the change in the objective function value corresponding to the current best individual is less than a preset threshold, or the number of iterations reaches a preset number.

8. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, The construction of the metamaterial topology structure based on the optimal mesh topology encoding includes: The optimal mesh topology code is analyzed to determine the material distribution and geometric configuration of the metamaterial structural unit; Based on the material distribution and geometric configuration, a corresponding metamaterial topology is constructed.

9. The method for designing a multi-degree-of-freedom special reflective metamaterial topology according to claim 1, characterized in that, The metamaterial topology is a three-layer structure.

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