An ultra-high frequency anti-metal RFID tag antenna packaging optimization method

Abstract

The application provides a packaging optimization method for a super high frequency metal-resistant RFID tag antenna, and belongs to the technical field of RFID tag antenna packaging. The method comprises the following steps: firstly, a composite equation group containing antenna current distribution, input impedance, radiation characteristics and metal backboard effect is established, and analytical solution is carried out to obtain the parameter range of each geometric parameter, material characteristic and metal backboard influence. Then, a multi-objective optimization model considering packaging parameters is established, and the optimized packaging parameters are solved by using a genetic algorithm, with the read distance, bandwidth, gain, efficiency and other indexes as the targets. Finally, actual super high frequency metal-resistant RFID tag antenna packaging design and production are carried out according to the optimization results. The method can effectively balance the antenna performance and the metal resistance capacity, provides a systematic solution for the design and optimization of the super high frequency metal-resistant RFID tag antenna, and solves the technical problem that the prior art is difficult to be systematically optimized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of RFID tag antenna packaging, and specifically relates to a packaging optimization method for an ultra-high frequency metal-resistant RFID tag antenna. BACKGROUND

[0002] Radio frequency identification (RFID) technology plays an increasingly important role in the era of the Internet of Things. Ultra-high frequency (UHF) RFID tags are widely used in fields such as logistics tracking, asset management, and supply chain optimization due to their long-range reading capabilities and low cost. However, when RFID tags are attached to metal surfaces or need to work in metal environments, their performance is severely affected. This is because metal surfaces cause electromagnetic wave reflection, absorption, and detuning effects, which reduce the reading distance and reliability of the tags.

[0003] To solve this problem, researchers have proposed various metal-resistant RFID tag design schemes. Common methods include using high dielectric constant materials as isolation layers, adopting special antenna structures (such as inverted F antennas, planar inverted F antennas, etc.), and using electromagnetic bandgap (EBG) structures. In addition, existing technologies provide metal-resistant capability by setting a layer of wave-absorbing material (magnetic conductive film) on the side of the metal-resistant RFID tag that contacts the metal. These methods improve the performance of RFID tags in metal environments to some extent, but still have some limitations.

[0004] Firstly, existing metal-resistant RFID tag designs usually require thick isolation layers or complex antenna structures, which increase the overall thickness and cost of the tags. Secondly, many design schemes can only work at specific frequencies or narrow bandwidths, making it difficult to meet the UHF RFID frequency band requirements in different regions around the world. Thirdly, existing design methods often rely on experience and repeated trials, lacking systematic and theoretical guidance, resulting in a time-consuming and inefficient design process.

[0005] In addition, existing technologies also face challenges in tag packaging. Packaging not only needs to protect the tag from environmental influences, but also has a significant impact on antenna performance. Inappropriate packaging design can lead to a decline in antenna performance, negating the advantages of carefully designed antenna structures. However, there is currently a lack of a systematic method to optimize the packaging design of RFID tags, especially in the context of considering metal environmental influences.

[0006] Therefore, there is an urgent need for a systematic method that can comprehensively consider antenna design, metal environmental influences, and packaging optimization to improve the performance and applicability of ultra-high frequency metal-resistant RFID tags. This method should be able to ensure tag miniaturization and low cost while achieving excellent reading distance, wideband characteristics, and stability, thereby meeting the growing demand for industrial Internet of Things applications. SUMMARY

[0007] Therefore, the application provides an encapsulation optimization method for an ultra-high frequency metal-resistant RFID tag antenna, which can solve the technical problem that the prior art is difficult to systematically optimize the encapsulation design of an RFID tag.

[0008] The application is implemented as follows:

[0009] The application provides an encapsulation optimization method for an ultra-high frequency metal-resistant RFID tag antenna, which comprises the following steps:

[0010] S10, a composite equation set containing geometric parameters of an ultra-high frequency metal-resistant RFID tag antenna, material properties and influences of a metal back plate is constructed, considering antenna current distribution, input impedance, radiation characteristics and mirror effects caused by the metal back plate, including current distribution equations, input impedance equations, radiation field equations, mirror current equations, surface current density equations, dielectric loss equations, metal back plate reflection coefficient equations, antenna gain equations and antenna efficiency equations;

[0011] S20, the composite equation set is analytically solved to obtain a plurality of analytical solutions, which are respectively an antenna length analytical solution, an antenna width analytical solution, an antenna thickness analytical solution, a dielectric layer thickness analytical solution, a metal back plate size analytical solution and an antenna-to-back plate spacing analytical solution, the geometric parameters, material properties and influences of the metal back plate and working frequencies and chip impedances are substituted into the plurality of analytical solutions to obtain a plurality of parameter ranges, which are respectively an antenna length range, an antenna width range, an antenna thickness range, a dielectric layer thickness range, a metal back plate size range and an antenna-to-back plate spacing range;

[0012] S30, a multi-objective optimization model considering encapsulation parameters is established based on performance indicators of the antenna, the performance indicators include reading distance, bandwidth, gain, efficiency, directivity and impedance matching degree, the plurality of analytical solutions and the plurality of parameter ranges are taken as constraint conditions of the multi-objective optimization model, and the encapsulation parameters include dielectric constant of encapsulation material, loss tangent of encapsulation material, encapsulation thickness, encapsulation size, encapsulation shape and encapsulation position;

[0013] S40, a genetic algorithm is used to take preset initial encapsulation parameters as an initial population, and iterative optimization is performed through selection, crossover and mutation operations to solve the multi-objective optimization model and obtain optimized encapsulation parameters;

[0014] S50, actual encapsulation design and production of the ultra-high frequency metal-resistant RFID tag antenna are performed according to the optimized encapsulation parameters.

[0015] The geometric parameters include: antenna length , antenna width , antenna thickness , medium layer thickness , metal backplate size , antenna to backplate spacing ;

[0016] The material properties include: antenna conductivity , medium layer relative permittivity , medium layer loss tangent , metal backplate conductivity ;

[0017] The metal backplate effects include: image effect, surface current distribution, reflection coefficient, skin depth.

[0018] Wherein, the current distribution equation, specifically represented as:

[0019] ;

[0020] In the formula, is the current at the z position on the antenna; is the current amplitude at the feed point; is the voltage amplitude at the feed point; is the wave number; is the operating wavelength; is the characteristic impedance; is the position coordinate along the antenna axis, is the imaginary unit, .

[0021] Wherein, the input impedance equation, specifically represented as:

[0022] ;

[0023] In the formula, is the input impedance; is the input resistance; is the input reactance; is the radiation resistance; is the loss resistance; is the antenna itself reactance; is the mutual inductance reactance caused by the metal backplate; Calculated by the following formula:

[0024] ;

[0025] Wherein is the radiation power, obtained by far field integration:

[0026] ;

[0027] Wherein, It is the electric field strength. It is the magnetic field strength. It is an integral surface. Indicates complex conjugation;

[0028] Calculated using conductor loss and dielectric loss:

[0029] ;

[0030] in For conductor loss, For dielectric loss, Angular frequency, The relative permittivity, The dielectric loss tangent, It is the antenna length. It is the conductor radius. It is skin depth, It refers to the volume of the medium.

[0031] The radiation field equation is specifically expressed as follows:

[0032] ;

[0033] ;

[0034] In the formula, Far-field electric field Quantity, Far-field magnetic field Quantity, Free-space wave impedance; The distance from the observation point to the antenna; The angle between the antenna axis and the antenna axis.

[0035] The image current equation is specifically expressed as follows:

[0036] ;

[0037] In the formula, It is the distance from the antenna to the metal backplate.

[0038] The surface current density equation is specifically expressed as follows:

[0039] ;

[0040] in It is the surface normal vector. It is the conductivity of the conductor. and These are the magnetic fields on both sides of the metal backplate. It is a tangential electric field.

[0041] wherein the medium loss equation is specifically expressed as:

[0042] ;

[0043] wherein is the angular frequency, is the vacuum permittivity, is the medium volume.

[0044] wherein the metal back plate reflection coefficient equation is specifically expressed as:

[0045] ;

[0046] wherein is the metal surface impedance, is the free space impedance, is the vacuum permeability.

[0047] wherein the antenna gain equation is specifically expressed as:

[0048] ;

[0049] wherein is the radiation intensity, is the input power.

[0050] wherein the antenna efficiency equation is specifically expressed as:

[0051] .

[0052] Specifically, the step S10 specifically comprises: constructing a composite equation set containing the geometric parameters, material properties and metal back plate influence of the super high frequency metal-resistant RFID tag antenna. The composite equation set comprises a current distribution equation, an input impedance equation, a radiation field equation, an image current equation, a surface current density equation, a medium loss equation, a metal back plate reflection coefficient equation, an antenna gain equation and an antenna efficiency equation. By establishing such a comprehensive mathematical model, the various performance indicators of the super high frequency metal-resistant RFID tag antenna can be comprehensively described, laying a foundation for subsequent parameter optimization.

[0053] The step S20 specifically comprises: analytically solving the compound equation set to obtain an analytical expression of the antenna length, width, thickness, dielectric layer thickness, backboard size and antenna-to-backboard spacing and the like. The analytical solution directly reflects the mutual relationship between the parameters, and provides a basis for subsequent parameter optimization. For example, the relationship between the antenna length and the working wavelength, the relationship between the antenna width and the working frequency and the dielectric constant, the relationship between the antenna thickness and the conductivity, the relationship between the dielectric layer thickness and the working wavelength and the dielectric constant, the relationship between the backboard size and the antenna size, and the relationship between the antenna-to-backboard spacing and the working wavelength and the like.

[0054] The step S30 specifically comprises: based on the read distance, bandwidth, gain, efficiency, directivity and impedance matching degree and the like, an antenna performance index, a multi-objective optimization model is established. The optimization function adopts the form of weighted sum, and each performance index sub-function is comprehensively considered. Meanwhile, the analytical solution of each parameter obtained in the step S20 and the value range thereof are taken as the constraint condition of the optimization model. In addition, the packaging parameters such as the dielectric constant, the loss tangent, the thickness, the size, the shape and the position of the packaging material are also taken into the optimization objective function for trade-off. Through the establishment of such a multi-objective optimization model, the optimal antenna parameters and packaging scheme can be found under the premise of meeting each performance index.

[0055] The step S40 specifically comprises: using a genetic algorithm to iteratively solve the multi-objective optimization problem established in the step S30. First, a set of initial packaging parameters is set as an initial population, and the fitness value is calculated. Then, selection, crossover, mutation and the like are adopted to generate new individuals and update the population until the preset termination condition is reached. Through the iterative optimization of the genetic algorithm, the optimal packaging parameter scheme meeting each performance index can be finally obtained. The heuristic optimization algorithm can effectively explore the solution space of the complex multi-objective optimization problem, and find a solution close to the global optimum.

[0056] The step S50 specifically comprises: according to the optimal packaging parameters obtained in the step S40, the actual packaging design and production of the ultra-high frequency metal-resistant RFID tag antenna are carried out. Specifically, it comprises determining the antenna geometric size, selecting the metal backboard, determining the antenna-to-backboard spacing, selecting the packaging material and size, assembling the packaging and performing performance test and the like. Through this series of actual packaging design and production process, the theoretical optimization result can be converted into an actually usable RFID tag antenna product. Meanwhile, the experience feedback accumulated in the production and test process can further improve the theoretical model and optimization method, and improve the reliability and accuracy of the design.

[0057] The compound equation set constructed in the step S10 further comprises the following contents:

[0058] 1) Current distribution equation: describes the distribution of current on the antenna, which directly affects the radiation characteristics of the antenna. This equation can represent the current amplitude, phase and axial variation of the antenna feed point.

[0059] 2) Input impedance equation: describes the input impedance of the antenna, including radiation resistance, loss resistance, antenna reactance and mutual inductance reactance caused by the metal back plate. The size and matching of the input impedance directly affect the working performance of the antenna.

[0060] 3) Radiation field equation: calculates the far-field electromagnetic field distribution of the antenna, which lays the foundation for the calculation of gain, directivity and other parameters. This equation can represent the electric field and magnetic field components of the antenna in any observation direction.

[0061] 4) Image current equation: describes the image current caused by the metal back plate, which affects the current distribution and input impedance of the antenna.

[0062] By establishing the above complex equation set, the performance indicators of the ultra-high frequency metal-resistant RFID tag antenna can be comprehensively described, which provides a basis for subsequent parameter optimization.

[0063] The analytical solution of the antenna geometric parameters obtained by solving the complex equation set in step S20 includes:

[0064] 1) Antenna length analytical solution: using the current distribution equation and the input impedance equation, the relationship between the antenna length and the working wavelength is obtained, and a correction coefficient of the end effect is introduced.

[0065] 2) Antenna width analytical solution: starting from the input impedance equation and the radiation field equation, the relationship between the antenna width and the working frequency and the dielectric constant is obtained, and a width correction coefficient is introduced.

[0066] 3) Antenna thickness analytical solution: based on the surface current density equation and the skin effect, the relationship between the antenna thickness and the conductivity is obtained, and a thickness coefficient is introduced.

[0067] 4) Dielectric layer thickness analytical solution: starting from the image current equation, the relationship between the dielectric layer thickness and the working wavelength and the dielectric constant is obtained, and a thickness correction coefficient is introduced.

[0068] Compared with the prior art, the packaging optimization method of the ultra-high frequency metal-resistant RFID tag antenna provided by the present application has the following advantages:

[0069] Firstly, the method establishes a complex equation set containing antenna geometric parameters, material properties and the influence of metal backplane, comprehensively considers current distribution, input impedance, radiation characteristics and mirror effect caused by metal backplane and other factors. This comprehensive theoretical model provides a solid foundation for subsequent optimization, making the design process more scientific and reliable.

[0070] Secondly, by analytically solving the complex equation set, the method obtains analytical solutions and parameter ranges of multiple key parameters. These analytical solutions not only provide theoretical guidance for initial design, but also greatly reduce the parameter search space and improve the efficiency of subsequent optimization. Compared with traditional empirical design or purely numerical optimization methods, this analytical-numerical combined method can converge to the optimal solution faster.

[0071] Thirdly, the method establishes a multi-objective optimization model considering packaging parameters, including read distance, bandwidth, gain, efficiency, directivity and impedance matching as optimization objectives. This multi-objective optimization strategy can achieve a good balance between various performance indicators, avoiding the decline of other performance caused by single performance optimization.

[0072] In addition, the method innovatively includes packaging parameters (such as packaging material dielectric constant, loss tangent, packaging thickness, size, shape and position) into the optimization model, realizing the collaborative optimization of antenna design and packaging design. This overall optimization strategy not only improves the overall performance of the tag, but also ensures that the packaged tag still maintains excellent anti-metal characteristics.

[0073] Through iterative optimization of genetic algorithm, the method can efficiently search for the optimal solution in complex parameter space. This intelligent optimization algorithm can handle nonlinear, multivariate optimization problems, overcoming the limitations of traditional design methods in dealing with complex interactions.

[0074] In summary, the present application solves the technical problem that the prior art is difficult to systematically optimize the packaging design of RFID tags. BRIEF DESCRIPTION OF DRAWINGS

[0075] Figure 1 The flowchart of the method provided by the present application. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0077] As Figure 1 shown is a packaging optimization method flowchart of an ultra-high frequency anti-metal RFID tag antenna provided by the present application, and the method comprises the following steps:

[0078] S10, construct a composite equation set containing the geometric parameters of the ultra-high frequency metal-resistant RFID tag antenna, material properties and the influence of the metal backboard, considering the antenna current distribution, input impedance, radiation characteristics and the mirror effect caused by the metal backboard, including current distribution equation, input impedance equation, radiation field equation, mirror current equation, surface current density equation, dielectric loss equation, metal backboard reflection coefficient equation, antenna gain equation and antenna efficiency equation;

[0079] S20, analytically solve the composite equation set to obtain a plurality of analytical solutions, which are respectively antenna length analytical solution, antenna width analytical solution, antenna thickness analytical solution, dielectric layer thickness analytical solution, metal backboard size analytical solution, antenna and backboard spacing analytical solution, and the geometric parameters, material properties and metal backboard influence and working frequency, chip impedance are substituted into the plurality of analytical solutions to obtain a plurality of parameter ranges, which are respectively antenna length range, antenna width range, antenna thickness range, dielectric layer thickness range, metal backboard size range, antenna and backboard spacing range;

[0080] S30, based on the performance index of the antenna, a multi-objective optimization model considering the packaging parameters is established, the performance index includes reading distance, bandwidth, gain, efficiency, directivity and impedance matching degree, and the plurality of analytical solutions and the plurality of parameter ranges are taken as the constraint conditions of the multi-objective optimization model, and the packaging parameters include packaging material dielectric constant, packaging material loss tangent, packaging thickness, packaging size, packaging shape and packaging position;

[0081] S40, using genetic algorithm, taking the preset initial packaging parameters as the initial population, iteratively optimizing through selection, crossover and mutation operations, solving the multi-objective optimization model, and obtaining the optimized packaging parameters;

[0082] S50, according to the optimized packaging parameters, the actual packaging design and production of the ultra-high frequency metal-resistant RFID tag antenna are carried out.

[0083] The specific implementation of the above steps is described in detail as follows:

[0084] Step S10: Construct a composite equation set containing the geometric parameters of the ultra-high frequency metal-resistant RFID tag antenna, material properties and the influence of the metal backboard

[0085] The purpose of this step is to establish a mathematical model that comprehensively considers the antenna geometric size, material properties and the influence of the metal backboard, laying a foundation for subsequent parameter optimization. Specifically, this composite equation set includes the following parts:

[0086] 1. Current distribution equation: describes the distribution of current on the antenna, which directly affects the radiation characteristics of the antenna.

[0087] 2. Input impedance equation: describes the input impedance of the antenna, including the radiation resistance, loss resistance, antenna reactance, and mutual inductance reactance caused by the metal backplate. The size and matching of the input impedance directly affect the performance of the antenna.

[0088] 3. Radiation field equation: calculates the far-field electromagnetic field distribution of the antenna, laying the foundation for the calculation of subsequent gain, directivity, and other parameters.

[0089] 4. Image current equation: describes the image current caused by the metal backplate, which affects the current distribution and input impedance of the antenna.

[0090] 5. Surface current density equation: calculates the current density distribution on the surface of the antenna, providing a basis for subsequent loss analysis.

[0091] 6. Dielectric loss equation: describes the power loss in the dielectric layer, which is an important part of the antenna efficiency.

[0092] 7. Metal backplate reflection coefficient equation: describes the reflection characteristics of the metal backplate to electromagnetic waves, affecting the radiation characteristics of the antenna.

[0093] 8. Antenna gain equation: calculates the directivity gain of the antenna, which is one of the important indicators to measure the performance of the antenna.

[0094] 9. Antenna efficiency equation: describes the overall efficiency of the antenna, including the radiation efficiency and matching efficiency.

[0095] By establishing such a comprehensive mathematical model, the performance indicators of the ultra-high frequency metal-resistant RFID tag antenna can be comprehensively described, providing a basis for subsequent parameter optimization.

[0096] Step S20: Analytically solving the complex equation set to obtain multiple analytical solutions

[0097] After establishing the complex equation set, the purpose of this step is to solve it to obtain the analytical expressions of each key parameter. This has the advantage of more clearly showing the relationship between each parameter, providing a basis for subsequent parameter optimization. Specifically, this step includes the following sub-steps:

[0098] 1. Solving the analytical solution of the antenna length: using the current distribution equation and the input impedance equation, the relationship between the antenna length and the operating wavelength can be obtained, and the correction coefficient of the end effect is introduced.

[0099] 2. Solving the analytical solution of the antenna width: starting from the input impedance equation and the radiation field equation, the antenna width With operating frequency and dielectric constant The relationship is established, and a width correction factor is introduced. .

[0100] 3. Analytical solution for antenna thickness: Based on the surface current density equation and skin effect, the antenna thickness can be obtained. With conductivity The relationship is established, and a thickness coefficient is introduced. .

[0101] 4. Solving for the analytical solution of the dielectric layer thickness: Starting from the image current equation, the dielectric layer thickness can be obtained. With operating wavelength and dielectric constant The relationship is established, and a thickness correction factor is introduced. .

[0102] 5. Analytical solution for the dimensions of the metal backplate: Based on the radiation field equation, the dimensions of the backplate can be obtained. The relationship with antenna size, and the introduction of a size factor. .

[0103] 6. Solving for the analytical solution of the antenna-backplane distance: Starting from the image current equation, the antenna-backplane distance can be obtained. With operating wavelength The relationship is established, and a spacing correction factor is introduced. .

[0104] Through the above steps, analytical expressions for the antenna length, width, thickness, dielectric layer thickness, backplane dimensions, and the distance between the antenna and the backplane were obtained. These parameters directly affect the antenna's performance indicators. These analytical solutions lay the foundation for subsequent parameter optimization.

[0105] Step S30: Establish a multi-objective optimization model considering packaging parameters based on antenna performance indicators.

[0106] The purpose of this step is to establish a multi-objective optimization model that considers both antenna performance metrics and packaging parameters. Specifically, it includes the following sub-steps:

[0107] 1. Define optimization objectives: These mainly include readout distance, bandwidth, gain, efficiency, directivity, and impedance matching. Each objective can be represented by a sub-objective function. To describe, such as reading distance ,bandwidth wait.

[0108] 2. Establish a multi-objective optimization model: Combine the above sub-objective functions to form a multi-objective optimization model. The form is a weighted sum:

[0109] ;

[0110] wherein are the weight coefficients of each objective, which can be adjusted according to actual needs.

[0111] 3. Determining the constraint conditions: taking the analytical solutions of each parameter and its value range obtained in step S20 as the constraint conditions of the multi-objective optimization model. This includes the length, width, thickness of the antenna, the thickness of the dielectric layer, the size of the back plate, and the distance between the antenna and the back plate, etc.

[0112] 4. Considering the packaging parameters: in addition to the above-mentioned geometric parameters and material properties, the influence of packaging on the performance of the antenna also needs to be considered. The packaging parameters include the dielectric constant, loss tangent, thickness, size, shape, and position of the packaging material, etc. These parameters also need to be included in the optimization objective function for trade-off.

[0113] By establishing such a multi-objective optimization model, the optimal antenna parameters and packaging scheme can be found under the premise of meeting various performance indicators, and the performance of the ultra-high frequency anti-metal RFID tag antenna is maximized.

[0114] Step S40: using the genetic algorithm, taking the preset initial packaging parameters as the initial population, and performing iterative optimization

[0115] The purpose of this step is to use the genetic algorithm to solve the multi-objective optimization problem established in step S30, and obtain the optimal packaging parameters. Genetic algorithm is an optimization algorithm that simulates biological evolution, and has good global search ability. The specific implementation process is as follows:

[0116] 1. Determining the initial population: first, a set of initial packaging parameters are needed as the initial population. These parameters include the dielectric constant, loss tangent, thickness, size, shape, and position of the packaging material, etc.

[0117] 2. Calculating the fitness: taking each individual (i.e. a set of packaging parameters) into the multi-objective optimization model established in step S30 , calculate its fitness value. The higher the fitness value, the better the performance of the packaging scheme corresponding to the individual.

[0118] 3. Selection operation: selecting individuals according to the fitness value, and retaining the better individuals for subsequent crossover and mutation operations. Common selection operators include roulette wheel selection, tournament selection, etc.

[0119] 4. Crossover operation: performing crossover operation on the selected individuals to generate new individuals. Crossover operation simulates the chromosome recombination process in biological evolution, and can produce new genetic characteristics.

[0120] 5. Mutation operation: randomly mutate the new individuals generated by crossover, simulating the genetic mutation process in biological evolution. Mutation operation can increase the diversity of the population, helping the algorithm to jump out of the local optimal solution.

[0121] 6. Next generation: put the newly generated individuals into the population, forming a new generation of population.

[0122] 7. Iterative optimization: repeat steps 3-6 until the pre-set termination condition (such as the number of iterations or the convergence of the objective function value) is reached.

[0123] Through the iterative optimization process of genetic algorithm, the optimal packaging parameter scheme that meets various performance indicators can be finally obtained. This heuristic optimization algorithm can effectively explore the solution space of complex multi-objective optimization problems and find solutions close to the global optimum.

[0124] Step S50: According to the optimized packaging parameters, the actual packaging design and production of the ultra-high frequency metal-resistant RFID tag antenna

[0125] After the parameter optimization in the above steps, the last step is to perform the actual packaging design and production of the ultra-high frequency metal-resistant RFID tag antenna according to the obtained optimal packaging parameter scheme. Specifically, it includes the following sub-steps:

[0126] 1. Determine the antenna and its geometric parameters: according to the antenna length , width , thickness , dielectric layer thickness and other parameters obtained in step S20, determine the specific size of the antenna.

[0127] 2. Select the size of the metal back plate: according to the back plate size obtained in step S20, select an appropriate metal back plate for production.

[0128] 3. Determine the distance between the antenna and the back plate: according to the distance between the antenna and the back plate obtained in step S20, reasonably fix the relative position of the antenna and the back plate.

[0129] 4. Select the packaging material and size: according to the optimal packaging parameters obtained in step S40, select appropriate packaging material and determine its thickness, size and shape.

[0130] 5. Assemble the package: assemble the antenna, metal back plate and packaging material according to the optimized parameters to form a complete ultra-high frequency metal-resistant RFID tag antenna.

[0131] 6. Performance test: test the finished RFID tag antenna for various performance parameters to verify whether it meets the expected indicators. If there is deviation, the parameters can be adjusted appropriately for optimization.

[0132] Through this series of actual packaging design and production process, the aforementioned theoretical optimization results can be converted into practical RFID tag antenna products. At the same time, the experience feedback accumulated in the production and testing process can further improve the aforementioned theoretical model and optimization method, and improve the reliability and accuracy of the design.

[0133] Specifically, the geometric parameters include: antenna length , antenna width , antenna thickness , dielectric layer thickness , metal backboard size , antenna and backboard spacing ;

[0134] The material properties include: antenna conductivity , dielectric layer relative permittivity , dielectric layer loss tangent , metal backboard conductivity ;

[0135] The metal backboard effect includes: mirror effect, surface current distribution, reflection coefficient, skin depth.

[0136] The following is the formula expression of each equation in the complex equation set:

[0137] 1. Current distribution equation:

[0138]

[0139] Where:

[0140] - current at z position on the antenna;

[0141] - feed point current amplitude;

[0142] - feed point voltage amplitude;

[0143] - wave number;

[0144] - working wavelength;

[0145] - characteristic impedance;

[0146] - the position coordinate along the antenna axis;

[0147] 2. The input impedance equation:

[0148] ;

[0149] where:

[0150] - the input impedance;

[0151] - the input resistance;

[0152] - the input reactance;

[0153] - the radiating resistance;

[0154] - the loss resistance;

[0155] - the antenna itself reactance;

[0156] - the mutual inductance reactance caused by the metal backplane;

[0157] It can be calculated by the following formula:

[0158] ;

[0159] where is the radiated power, which can be obtained by far-field integration:

[0160] ;

[0161] It can be calculated by conductor loss and dielectric loss:

[0162] ;

[0163] where is the antenna length, is the conductor radius, is the skin depth, is the dielectric volume.

[0164] 3. The radiation field equation:

[0165] The far-field and components can be expressed as:

[0166] ;

[0167] ;

[0168] where:

[0169] - free space wave impedance;

[0170] - distance from observation point to antenna;

[0171] - angle with antenna axis;

[0172] - antenna length;

[0173] 4. Image current equation:

[0174] ;

[0175] where is the distance from antenna to metal backplane.

[0176] 5. Surface current density equation:

[0177] ;

[0178] where is the surface normal vector, and are the magnetic fields on either side of the metal backplane, is the tangential electric field.

[0179] 6. Dielectric loss equation:

[0180] ;

[0181] where is the angular frequency, is the vacuum permittivity, is the dielectric volume.

[0182] 7. Metal backplane reflection coefficient equation:

[0183] ;

[0184] where is the metal surface impedance, is the free space impedance.

[0185] 8. Antenna gain equation:

[0186] ;

[0187] where is the radiated intensity, is the input power.

[0188] 9. Antenna efficiency equation:

[0189] ;

[0190] Starting from the basic set of composite equations, the analytical solution of each parameter is derived step by step as follows:

[0191] 1. Antenna length analytical solution:

[0192] First, consider the current distribution equation and the input impedance equation:

[0193] ;

[0194] ;

[0195] For a half-wavelength dipole, it is known that at resonance , and . Therefore:

[0196] ;

[0197] ;

[0198] Combining these two equations, we get:

[0199] ;

[0200] Considering the end effect in practical cases, introduce the correction coefficient :

[0201] ;

[0202] where is usually between 0.9 and 0.95, which can be determined by solving the complete electromagnetic field equation or experimental measurement.

[0203] 2. Antenna width analytical solution:

[0204] Antenna width mainly affects the bandwidth. Starting from the input impedance equation and the radiation field equation:

[0205] ;

[0206] ;

[0207] The bandwidth is related to the rate of change of input impedance. It can be approximately considered that:

[0208] ;

[0209] where is the effective dielectric constant, which can be approximated as:

[0210] ;

[0211] Combining these equations, we can obtain the analytical solution for the antenna width:

[0212] ;

[0213] where is the width correction factor, typically between 0.05 and 0.1.

[0214] 3. Analytical solution for antenna thickness:

[0215] Antenna thickness mainly affects the loss. Starting from the surface current density equation and the skin effect:

[0216] ;

[0217] The skin depth is defined as:

[0218] ;

[0219] To ensure good conductivity, the actual thickness should be greater than the skin depth:

[0220] ;

[0221] where is the thickness factor, typically greater than 3.

[0222] 4. Analytical solution for dielectric layer thickness:

[0223] The dielectric layer thickness affects the coupling between the antenna and the metal backplate. Starting from the image current equation:

[0224] ;

[0225] To achieve the best performance, we want the antenna current and the image current to be out of phase. This happens when:

[0226] ;

[0227] Solving this equation, we get:

[0228] ;

[0229] Considering the effect of the dielectric, we introduce the effective wavelength , which gives us:

[0230] ;

[0231] where is the thickness correction factor, usually between 0.8 and 1.2.

[0232] 5. Metal backplate size analytical solution:

[0233] The metal backplate size mainly affects the radiation characteristics of the antenna. Starting from the radiation field equation:

[0234] ;

[0235] To ensure good shielding effect, the backplate size should be larger than the antenna size. It can be approximated as:

[0236] ;

[0237] where is the size correction factor, usually greater than 1.2.

[0238] 6. Antenna and backplate spacing analytical solution:

[0239] The antenna and backplate spacing affects the image effect. Starting from the image current equation:

[0240] ;

[0241] To obtain the best gain, we hope that the antenna current and the image current are opposite in phase:

[0242] ;

[0243] Solving this equation, we get:

[0244] ;

[0245] where is the spacing correction factor, usually between 0.9 and 1.1.

[0246] These analytical solutions give the initial estimated values and ranges of each parameter. In the actual optimization process, the mutual influence and constraints between these parameters need to be considered. For example, the antenna length and width will affect the input impedance, and then affect the impedance matching. The thickness of the dielectric layer and the spacing between the antenna and the backplate will jointly affect the radiation characteristics of the antenna.

[0247] To get more accurate solutions, these interactions need to be considered, and numerical methods (such as the method of moments) may be needed to solve Maxwell's equations to get more accurate current distribution and input impedance. Then, through an iterative optimization process, such as genetic algorithm, to find the best combination of parameters that meet all performance indicators.

[0248] The following is a multi-objective optimization model:

[0249] ;

[0250] where are the weights of each objective, each sub-objective function can be defined as follows:

[0251]

[0252]

[0253]

[0254]

[0255]

[0256]

[0257] Here is the reading distance, is the bandwidth, is the gain, is the efficiency, is the directivity, is the reflection coefficient. Subscript denotes the required value, denotes the maximum possible value.

[0258] In summary, this invention involves the application of numerous mathematics, electromagnetics and optimization algorithms. First, a complex equation set is established, which comprehensively considers the antenna geometric parameters, material properties and the influence of metal back plate, laying the foundation for subsequent parameter optimization. Then, the complex equation set is analytically solved, and the analytical expressions of each key parameter are obtained. On this basis, a multi-objective optimization model is established, which balances the antenna performance combined with the packaging parameters. Finally, the genetic algorithm is used to iteratively solve the optimization problem, and the optimal packaging scheme is obtained. The entire design process is closely linked, fully utilizing mathematical modeling, analytical solution and heuristic optimization algorithms and other technical means, and realizing the optimization design of the performance of the ultra-high frequency anti-metal RFID tag antenna.

[0259] ​​​​​​Specifically, the principle of the present application is that first, the method constructs a composite equation set containing antenna geometric parameters, material properties and the influence of metal backplane to comprehensively describe the performance indicators of RFID tag antenna. Among them, the current distribution equation describes the distribution of current on the antenna, which directly affects the radiation characteristics of the antenna; the input impedance equation describes the input impedance of the antenna, including radiation resistance, loss resistance, etc., which affects the matching characteristics of the antenna; the radiation field equation calculates the far-field electromagnetic field distribution of the antenna, laying the foundation for the calculation of subsequent gain, directivity and other parameters; the image current equation describes the mirror current caused by the metal backplane, which will affect the current distribution and input impedance of the antenna; the surface current density equation, dielectric loss equation, metal backplane reflection coefficient equation, etc. are related to the loss characteristics of the antenna and the influence of metal.

[0260] Secondly, for the above composite equation set, the method uses an analytical solution method to obtain analytical expressions of the antenna length, width, thickness, dielectric layer thickness, backplane size and antenna-to-backplane spacing. These analytical solutions directly reflect the mutual relationship between the parameters, providing a basis for subsequent parameter optimization. For example, the relationship between the antenna length and the working wavelength, the relationship between the antenna width and the working frequency and the dielectric constant, the relationship between the antenna thickness and the conductivity, the relationship between the dielectric layer thickness and the working wavelength and the dielectric constant, the relationship between the backplane size and the antenna size, and the relationship between the antenna-to-backplane spacing and the working wavelength, etc.

[0261] On this basis, the method establishes a multi-objective optimization model, considering the read distance, bandwidth, gain, efficiency, directivity and impedance matching degree and other antenna performance indicators. In addition, the packaging parameters such as the dielectric constant, loss tangent, thickness, size, shape and position of the packaging material are also included in the optimization objective function. By using genetic algorithm for iterative optimization, the optimal antenna parameters and packaging scheme can be found under the premise of meeting various performance indicators.

[0262] Compared with the prior art, the technical scheme of the present application has the following advantages: 1) a comprehensive mathematical model is established, which can accurately describe the relationship between antenna performance and parameters; 2) analytical solution method is used to obtain the optimization range of each parameter, laying the foundation for subsequent parameter optimization; 3) a multi-objective optimization framework is adopted to realize the comprehensive trade-off between antenna performance indicators and packaging parameters; 4) with the help of intelligent optimization algorithms such as genetic algorithm, complex multi-objective optimization problems can be effectively explored to find solutions close to the global optimum.

[0263] In summary, the ultra-high frequency anti-metal RFID tag antenna packaging optimization method proposed by the present application systematically researches and innovates from mathematical modeling, parameter optimization to actual packaging design, etc., providing an effective technical path to solve the problem of poor performance of existing RFID tags working on metal surfaces.

[0264] The following is an example of a specific application scenario of the present invention: A company's R&D team, addressing the need for RFID systems on metal surfaces, decided to develop an ultra-high frequency anti-metal RFID tag antenna. Based on the packaging optimization method proposed in this invention, they implemented the following specific steps:

[0265] 1. Construct a system of composite equations

[0266] The research and development team first established a set of composite equations that included antenna geometry parameters, material properties, and the influence of the metal backplate. Specifically, this included:

[0267] (1) Current distribution equation:

[0268] ;

[0269] in, Indicates the antenna Current at location The current amplitude at the feed point. The voltage amplitude at the feed point. For wave number, For the operating wavelength, Characteristic impedance, These are the position coordinates along the antenna axis.

[0270] (2) Input impedance equation:

[0271] ;

[0272] in, For input impedance, For input resistance, For input reactance, For radiation resistance, For loss resistance, For the antenna's own reactance, Mutual inductance caused by the metal backplate.

[0273] (3) Radiation field equation:

[0274] Far field and The component can be represented as:

[0275] ;

[0276] ;

[0277] in, For free space wave impedance, The distance from the observation point to the antenna, is the angle between the antenna axis and the normal to the surface of the antenna, is the length of the antenna.

[0278] (4) Image current equation:

[0279] ;

[0280] where, is the distance from the antenna to the metal backing plate.

[0281] (5) Surface current density equation:

[0282] ;

[0283] where, is the surface normal vector, and are the magnetic fields on either side of the metal backing plate, is the tangential electric field.

[0284] (6) Dielectric loss equation:

[0285] ;

[0286] where, is the angular frequency, is the vacuum permittivity, is the relative permittivity, is the dielectric loss tangent, is the dielectric volume.

[0287] (7) Metal backing plate reflection coefficient equation:

[0288] ;

[0289] where, is the metal surface impedance, is the free space impedance, is the metal conductivity.

[0290] (8) Antenna gain equation:

[0291] ;

[0292] where, is the radiated intensity, is the input power.

[0293] (9) Antenna efficiency equation:

[0294] ;

[0295] where, is the radiated power.

[0296] By establishing such a comprehensive mathematical model, the R&D team can comprehensively describe various performance indicators of the ultra-high frequency metal-resistant RFID tag antenna.

[0297] 2. Solve the compound equation

[0298] After establishing the compound equation, the R&D team analytically solves it to obtain the optimization range of each key parameter:

[0299] (1) Antenna length analytical solution:

[0300] Considering the relationship between the antenna length and the working wavelength , . Therefore, we have:

[0301] ;

[0302] Where is the speed of light, is the working frequency. Considering the end effect in actual situations, introduce the correction coefficient , then the antenna length can be expressed as:

[0303] ;

[0304] (2) Antenna width analytical solution:

[0305] Antenna width mainly affects the bandwidth. We can get:

[0306] ;

[0307] Where is the relative dielectric constant of the medium, is the width correction coefficient.

[0308] (3) Antenna thickness analytical solution:

[0309] To ensure good electrical conductivity, the antenna thickness should be greater than the skin depth . According to:

[0310] ;

[0311] Where is the angular frequency, is the magnetic permeability, is the electrical conductivity. Take the thickness coefficient , then we have:

[0312] ;

[0313] (4) Analytical solution of the thickness of the dielectric layer:

[0314] For the best performance, the antenna current and the mirror current should be opposite in phase. According to , we have:

[0315] ;

[0316] Considering the effect of the dielectric, the effective wavelength is introduced, and we have:

[0317] ;

[0318] where is the thickness correction coefficient.

[0319] (5) Analytical solution of the size of the metal back plate:

[0320] To ensure good shielding effect, the size of the back plate should be larger than the size of the antenna. It can be approximated as:

[0321] ;

[0322] where is the size correction coefficient.

[0323] (6) Analytical solution of the distance between the antenna and the back plate:

[0324] To obtain the best gain, we hope that the antenna current and the mirror current are opposite in phase, i.e. . We have:

[0325] ;

[0326] where is the distance correction coefficient.

[0327] Through the above analytical solutions, the research and development team obtained the optimization range of each key parameter, which provides a basis for subsequent multi-objective optimization.

[0328] 3. Establishment of a multi-objective optimization model

[0329] Based on the above complex equation set and its analytical solutions, the research and development team established a multi-objective optimization model considering the antenna performance indicators and packaging parameters:

[0330] ;

[0331] where each sub-objective function is defined as follows:

[0332] ;

[0333] ;

[0334] ;

[0335] ;

[0336] ;

[0337] ;

[0338] wherein, is the read distance, is the bandwidth, is the gain, is the efficiency, is the directivity, is the reflection coefficient. The subscript denotes the required value, denotes the maximum possible value. is the weight coefficient of each target.

[0339] At the same time, the analytical solution of each parameter obtained in step 2 and its value range are taken as the constraint conditions of the optimization model. In addition, the packaging parameters such as the dielectric constant , the loss tangent , the thickness , the size , the shape and the position of the packaging material are also taken into consideration in the comprehensive consideration of the optimization objective function.

[0340] 4. Optimization using genetic algorithm

[0341] After establishing the multi-objective optimization model, the research and development team uses genetic algorithm to solve it. The specific steps are as follows:

[0342] (1) Set the initial population: first randomly generate a set of packaging parameters as the initial population, including , , mm, , the packaging shape is rectangular, and the packaging position is 20 mm away from the center of the antenna.

[0343] (2) Calculate the fitness: bring each individual (i.e. a set of packaging parameters) into the optimization function , calculate its fitness value. The higher the fitness value, the better the performance of the scheme.

[0344] (3) Selection operation: select the individual according to the fitness value, and keep the better individual for subsequent crossover and mutation operation. The tournament selection operator is used, and the selection probability is proportional to the fitness.

[0345] (4) Crossover operation: the selected individuals are subjected to crossover operation to generate new individuals. Single-point crossover is adopted, and crossover is performed with a probability of 50%.

[0346] (5) Mutation operation: the newly generated individuals are subjected to random mutation. The mutation probability is set to 10%, and mainly involves slight perturbation of the packaging parameters.

[0347] (6) Substitution of the next generation: the newly generated individuals are substituted into the population to form a new generation of population.

[0348] (7) Iterative optimization: repeat steps 3-6 above until the preset termination condition (such as the number of iterations or the convergence of the objective function value) is reached.

[0349] Through the iterative optimization of the above genetic algorithm, the research and development team finally obtained the optimal packaging scheme that meets all performance indicators: 、 、 mm、 , the packaging shape is rectangular, and the packaging position is 18 mm away from the center of the antenna.

[0350] 5. Implementing packaging design

[0351] According to the optimal packaging parameters obtained by optimization, the research and development team carried out the following actual packaging design and production:

[0352] (1) Antenna parameter design:

[0353] According to the analytical solution in step 2, the antenna length is determined to be mm, the width is mm, and the thickness is mm. The thickness of the dielectric layer is mm, and polytetrafluoroethylene (PTFE) material with a relative dielectric constant of and a loss tangent of is used.

[0354] (2) Metal backplate design:

[0355] The backplate size is , and aluminum alloy material with a conductivity of S / m is used. The distance between the antenna and the backplate is mm.

[0356] (3) Packaging design:

[0357] The packaging material is polyethylene terephthalate (PET) plastic with a relative dielectric constant of and a loss tangent of . The packaging thickness is mm, and the size The rectangular package is adopted, and the package position is 18mm away from the center of the antenna.

[0358] (4) Performance test:

[0359] The research and development team uses a Vector Network Analyzer to perform detailed tests on the completed RFID tag antenna, and measures parameters such as impedance, gain, radiation efficiency, etc. After debugging and optimization, the RFID tag antenna finally has a reading distance of 8m on a metal surface, a 3dB beam width of 60°, a maximum gain of 5.2dBi, and a radiation efficiency of 85%. These performance indicators all meet or exceed the expected requirements, verifying the effectiveness of the method of the application.

[0360] The above merely describes specific embodiments of the application, but the protection scope of the application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the application, which should all be encompassed within the protection scope of the application.

Claims

1. A method for optimizing the packaging of an ultra-high frequency anti-metal RFID tag antenna, characterized in that, Includes the following steps: S10. Construct a composite set of equations that includes the geometric parameters, material properties and the influence of the metal backplate of the UHF anti-metal RFID tag antenna, considering the antenna current distribution, input impedance, radiation characteristics and the image effect caused by the metal backplate, including the current distribution equation, input impedance equation, radiation field equation, image current equation, surface current density equation, dielectric loss equation, metal backplate reflection coefficient equation, antenna gain equation and antenna efficiency equation. S20. Solve the composite equations analytically to obtain multiple analytical solutions, namely, analytical solutions for antenna length, antenna width, antenna thickness, dielectric layer thickness, metal backplane size, and antenna-backplane spacing. Substitute geometric parameters, material properties, the influence of the metal backplane, operating frequency, and chip impedance into the multiple analytical solutions to obtain multiple parameter ranges, namely, antenna length range, antenna width range, antenna thickness range, dielectric layer thickness range, metal backplane size range, and antenna-backplane spacing range. S30. Establish a multi-objective optimization function considering packaging parameters based on antenna performance indicators. The performance indicators include readout distance, bandwidth, gain, efficiency, directivity, and impedance matching. The multiple analytical solutions and multiple parameter ranges are used as constraints of the multi-objective optimization model. The packaging parameters include the dielectric constant of the packaging material, the loss tangent of the packaging material, the packaging thickness, the packaging size, the packaging shape, and the packaging position. S40. Using a genetic algorithm, with preset initial encapsulation parameters as the initial population, iterative optimization is performed through selection, crossover, and mutation operations to solve the multi-objective optimization function and obtain the optimized encapsulation parameters. S50. Based on the optimized packaging parameters, perform the actual packaging design and fabrication of the ultra-high frequency anti-metal RFID tag antenna.

2. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 1, characterized in that, The current distribution equation is specifically expressed as follows: ； In the formula, Let be the current at position z on the antenna; This refers to the amplitude of the feed point current. This refers to the voltage amplitude at the feed point. Wave number; The operating wavelength; Characteristic impedance; Here are the position coordinates along the antenna axis. The imaginary unit, .

3. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 2, characterized in that, The input impedance equation is specifically expressed as follows: ； In the formula, Input impedance; Input resistance; Input reactance; Radiation resistance; For loss resistance; The reactance of the antenna itself; The mutual inductance caused by the metal backplate; Calculated using the following formula: ； in It is the radiated power, obtained through far-field integration: ； in, It is the electric field strength. It is the magnetic field strength. It is an integral surface. Indicates complex conjugation; Calculated using conductor loss and dielectric loss: ； in For conductor loss, For dielectric loss, Angular frequency, The relative permittivity, The dielectric loss tangent, It is the antenna length. It is the conductor radius. It is skin depth, It refers to the volume of the medium.

4. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 3, characterized in that, The radiation field equation is specifically expressed as follows: ； ； In the formula, Far-field electric field Quantity, Far-field magnetic field Quantity, Free-space wave impedance; The distance from the observation point to the antenna; The angle between the antenna axis and the antenna axis.

5. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 4, characterized in that, The image current equation is specifically expressed as follows: ； In the formula, It is the distance from the antenna to the metal backplate.

6. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 5, characterized in that, The surface current density equation is specifically expressed as follows: ； in It is the surface normal vector. It is the conductivity of the conductor. and These are the magnetic fields on both sides of the metal backplate. It is a tangential electric field.

7. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 6, characterized in that, The dielectric loss equation is specifically expressed as follows: ； in It is angular frequency. It is the vacuum permittivity. It refers to the volume of the medium.

8. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 7, characterized in that, The equation for the reflection coefficient of the metal backplate is specifically expressed as follows: ； in It is the surface impedance of the metal. It is free space impedance. It is the vacuum permeability. is the electrical conductivity of the metal.

9. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 8, characterized in that, The antenna gain equation is specifically expressed as follows: ； in It is the radiation intensity. It is the input power.

10. The packaging optimization method for an ultra-high frequency anti-metal RFID tag antenna according to claim 9, characterized in that, The antenna efficiency equation is specifically expressed as follows: 。

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