Simulation Method, System and Related Equipment of Surface Acoustic Wave Devices

Abstract

The present invention is applicable to the field of communication technologies, and particularly relates to a simulation method, system and related equipment for surface acoustic wave devices. The present invention obtains the test response parameters of a surface acoustic wave device; based on a first preset algorithm, an accurate simulation model of the surface acoustic wave device is established, and the geometric design parameters corresponding to each resonator are used as inputs of the accurate simulation model of the surface acoustic wave device for calculation to obtain the simulation response parameters corresponding to each resonator; based on a second preset algorithm, the accurate simulation model of the surface acoustic wave device is iteratively optimized according to an error function to obtain an optimized accurate simulation model of the surface acoustic wave; the simulation result is obtained through the optimized accurate simulation model of the surface acoustic wave. Compared with the prior art, the present invention can effectively reduce the simulation influence of surface acoustic wave devices caused by process errors and changes in packaging and testing environments during the production process, improve the design efficiency of surface acoustic wave devices, and reduce the cost of repeated production and testing.

Description

Technical Field

[0001] The present invention is applicable to the field of communication technologies, and particularly relates to a simulation method, system and related equipment for surface acoustic wave devices. Background Art

[0002] Surface acoustic wave filters are an important part of the radio frequency front-end in the communication industry and are widely used due to their excellent frequency selectivity, low power consumption, small size and other advantages. In the design and manufacture of surface acoustic wave filters, simulation technology plays a crucial role. Accurate simulation can help designers optimize the performance of the filters. Accurate simulation models of surface acoustic wave filters include finite element analysis (FEM), finite element / boundary element method (FEM / BEM), hierarchical cascade algorithm (HCT), etc. These models are based on the basic physical laws of the system and describe the behavior of the system by combining multiple physical fields such as mechanics and electricity. By selecting appropriate material parameters, adjusting the geometric structure of the device, including finger width, finger pitch, number of interdigital fingers, etc., and setting boundary conditions, the response parameters of the surface acoustic wave device can be simulated and calculated, so as to predict its actual performance, reduce repeated experiments in actual production, and save costs and time.

[0003] However, the accuracy of the model simulation results of surface acoustic wave devices is closely related to material parameters. Although multiple documents have verified and published the material parameters obtained under experimental conditions, these parameters do not calculate very accurate results in actual applications. Especially in high-frequency applications, there are large deviations between the simulation and test results, which limits their applications to a certain extent. The reasons for the simulation-test differences include: process errors generated during the wafer production process of the device, small differences from the actual situation caused by the simplification of the device simulation conditions, performance impacts brought about by changes in the packaging and test environment, etc.

[0004] Therefore, there is an urgent need for a new simulation method, system and related equipment for surface acoustic wave devices to solve the above technical problems. Summary of the Invention

[0005] The present invention provides a simulation method, system and related equipment for surface acoustic wave devices, aiming to improve the simulation cost and efficiency of surface acoustic wave devices.

[0006] In a first aspect, the present invention provides a simulation method for surface acoustic wave devices, and the simulation method includes the following steps:

[0007] S1. Obtain the test response parameters of the surface acoustic wave device; wherein, the surface acoustic wave device includes a plurality of resonators with different geometric design parameters;

[0008] S2. Establish an accurate simulation model of the surface acoustic wave device based on the first preset algorithm, use the geometric design parameters corresponding to each resonator as the input of the accurate simulation model of the surface acoustic wave device for calculation, and obtain the simulation response parameters corresponding to each resonator;

[0009] S3. Establish an error function based on the resonance frequency points and anti-resonance frequency points in the test response parameters and the resonance frequency points and anti-resonance frequency points in the simulation response parameters, and iteratively optimize the accurate simulation model of the surface acoustic wave device based on the error function according to the second preset algorithm to obtain an optimized accurate simulation model of the surface acoustic wave;

[0010] S4. Use the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as the input of the optimized accurate simulation model of the surface acoustic wave device for simulation to obtain a simulation result.

[0011] Preferably, in step S3, the following steps are included:

[0012] S31. Calculate a first center point according to the resonance frequency points and anti-resonance frequency points in the test response parameters, use the area within a preset range of the first center point as the first fundamental frequency region, and extract the extreme points in the first fundamental frequency region as the first characteristic points;

[0013] S32. Calculate a second center point according to the resonance frequency points and anti-resonance frequency points in the simulation response parameters, use the area within a preset range of the second center point as the second fundamental frequency region, and extract the extreme points in the second fundamental frequency region as the second characteristic points;

[0014] S33. Calculate the error function according to the first characteristic points and the second characteristic points;

[0015] S34. Define the coefficient corresponding to the material parameters of the resonator as a fitting parameter, and iteratively optimize the fitting parameter according to the error function by the second preset algorithm to obtain an optimized fitting parameter; wherein, the material parameters include a piezoelectric substrate material and a metal electrode material;

[0016] S35. Optimize the accurate simulation model of the surface acoustic wave according to the optimized fitting parameter to obtain the optimized accurate simulation model of the surface acoustic wave.

[0017] Preferably, in step S2, the simulation response parameters are processed and calculated based on the following relationship:

[0018] ;

[0019] Wherein, represents the elastic constant, represents the piezoelectric constant, represents density, represents dielectric constant, represents displacement, represents electric field, represents strain.

[0020] Preferably, in step S34, the following relationship is satisfied between the fitting parameters and the material parameters:

[0021] ;

[0022] wherein, represents the density fitting parameter, represents the elastic constant fitting parameter, represents the piezoelectric constant fitting parameter, represents the dielectric constant fitting parameter, represents the first imaginary fitting parameter, represents the second imaginary fitting parameter, represents an imaginary number.

[0023] Preferably, the error function is defined as , and the error function satisfies the following relationship:

[0024] ;

[0025] wherein, represents the amplitude error weight coefficient, represents the frequency error weight coefficient, represents the number of the resonators, represents the amplitude of the second characteristic point, represents the amplitude of the first characteristic point, represents the frequency of the second characteristic point, represents the frequency of the first characteristic point.

[0026] Preferably, the first preset algorithm includes one or more of the finite element method, the finite element / boundary element method, and the hierarchical cascade algorithm.

[0027] Preferably, the second preset algorithm includes one or more of the genetic algorithm, the particle swarm optimization algorithm, and the simulated annealing algorithm.

[0028] In a second aspect, the present invention further provides a simulation system for a surface acoustic wave device, including:

[0029] a test module for obtaining test response parameters of the surface acoustic wave device; wherein, the surface acoustic wave device includes a plurality of resonators having different geometric design parameters;

[0030] A simulation parameter calculation module, configured to establish an accurate simulation model of a surface acoustic wave device based on a first preset algorithm, calculate by using the geometric design parameters corresponding to each resonator as inputs of the accurate simulation model of the surface acoustic wave device, and obtain simulation response parameters corresponding to each resonator;

[0031] An iterative optimization module, configured to establish an error function according to the test response parameters and the simulation response parameters, and iteratively optimize the accurate simulation model of the surface acoustic wave device based on the error function by using a second preset algorithm to obtain an optimized accurate simulation model of the surface acoustic wave device;

[0032] A simulation module, configured to perform simulation by using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as inputs of the optimized accurate simulation model of the surface acoustic wave device, and obtain a simulation result.

[0033] In a third aspect, the present invention further provides a computer device, including: a memory, a processor, and a simulation program of a surface acoustic wave device stored on the memory and executable on the processor, where when the processor executes the simulation program of the surface acoustic wave device, the steps in the simulation method of the surface acoustic wave device according to any one of the foregoing embodiments are implemented.

[0034] In a fourth aspect, the present invention further provides a computer-readable storage medium, where a simulation program of a surface acoustic wave device is stored on the computer-readable storage medium, and when the simulation program of the surface acoustic wave device is executed by a processor, the steps in the simulation method of the surface acoustic wave device according to any one of the foregoing embodiments are implemented.

[0035] Compared with the prior art, the present invention obtains test response parameters of a surface acoustic wave device, where the surface acoustic wave device includes a plurality of resonators with different geometric design parameters; establishes an accurate simulation model of the surface acoustic wave device based on a first preset algorithm, calculates by using the geometric design parameters corresponding to each resonator as inputs of the accurate simulation model of the surface acoustic wave device, and obtains simulation response parameters corresponding to each resonator; establishes an error function according to the test response parameters and the simulation response parameters, and iteratively optimizes the accurate simulation model of the surface acoustic wave device based on the error function by using a second preset algorithm to obtain an optimized accurate simulation model of the surface acoustic wave device; performs simulation by using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as inputs of the optimized accurate simulation model of the surface acoustic wave device, and obtains a simulation result. The present invention can effectively reduce the simulation influence of the surface acoustic wave device caused by process errors and changes in the packaging and testing environment during the production process, improve the design efficiency of the surface acoustic wave device, and reduce the cost of repeated production and testing. Description of the Drawings

[0036] The present invention will be described in detail below with reference to the accompanying drawings. Through the detailed description in conjunction with the following drawings, the above or other aspects of the present invention will become clearer and easier to understand. In the drawings:

[0037] Figure 1 is a flowchart of a simulation method for a surface acoustic wave device provided by an embodiment of the present invention;

[0038] Figure 2 is a schematic diagram of a first fundamental frequency region of a simulation method for a surface acoustic wave device provided by an embodiment of the present invention;

[0039] Figure 3 is a simulation test comparison diagram of response parameters of a simulation method for a surface acoustic wave device provided by an embodiment of the present invention;

[0040] Figure 4 is a simulation test comparison diagram of response parameters of a surface acoustic wave dual-mode device of a simulation method for a surface acoustic wave device provided by an embodiment of the present invention;

[0041] Figure 5 is a schematic structural diagram of a simulation system for a surface acoustic wave device provided by an embodiment of the present invention;

[0042] Figure 6 is a schematic structural diagram of a computer device provided by an embodiment of the present invention. Specific Embodiments

[0043] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] Embodiment 1

[0045] Please refer to Figures 1 - 4 , the present invention provides a simulation method for a surface acoustic wave device, and the simulation method for the surface acoustic wave device includes the following steps:

[0046] S1. Obtain the test response parameters of the surface acoustic wave device; wherein, the surface acoustic wave device includes a plurality of resonators with different geometric design parameters.

[0047] In an embodiment of the present invention, the test response parameters of the surface acoustic wave device are obtained by testing with other surface acoustic wave devices under similar process conditions and similar test conditions. Similar process conditions refer to that the surface acoustic wave device has clearly defined process flows and parameters, has a determined application scenario, and usually belongs to a batch of wafer runs. Similar test conditions refer to that in the test stage, all surface acoustic wave devices are tested under the same external environment and measurement equipment to obtain test results in a short time. The test response parameters include admittance parameters and scattering parameters, and the geometric design parameters include parameters such as finger period, metallization rate, and aperture.

[0048] S2. Establish an accurate simulation model of the surface acoustic wave device based on a first preset algorithm, and use the geometric design parameters corresponding to each resonator as the input of the accurate simulation model of the surface acoustic wave device for calculation to obtain the simulation response parameters corresponding to each resonator.

[0049] In an embodiment of the present invention, the simulation response parameters are admittance parameters and simulation parameters, and the first preset algorithm includes one or more of the finite element method, the finite element / boundary element method, and the hierarchical cascade algorithm. Of course, it is not limited to the above algorithms, and other algorithms are also feasible.

[0050] In an embodiment of the present invention, in step S2, the simulation response parameters are processed and calculated based on the following relationship (piezoelectric physical equation):

[0051] ; (1)

[0052] Wherein, represents the elastic constant, represents the piezoelectric constant, represents the density, represents the dielectric constant, represents the displacement ( is the second derivative), represents the electric field, represents the strain. 、 and are all expressions.

[0053] S3. Establish an error function based on the resonance frequency points and anti-resonance frequency points in the test response parameters and the resonance frequency points and anti-resonance frequency points in the simulation response parameters, and iteratively optimize the accurate simulation model of the surface acoustic wave device based on the second preset algorithm according to the error function to obtain an optimized accurate simulation model of the surface acoustic wave.

[0054] In an embodiment of the present invention, the second preset algorithm includes one or more of a genetic algorithm, a particle swarm optimization algorithm, and a simulated annealing algorithm. Of course, it is not limited to the above algorithms, and other algorithms are also feasible.

[0055] In an embodiment of the present invention, in step S3, the following steps are included:

[0056] S31. Calculate a first center point according to the resonance frequency point and the anti-resonance frequency point in the test response parameters, and use the area of the first center point within a preset range as the first fundamental frequency region, and extract the extreme points in the first fundamental frequency region as the first feature points (that is, select the obvious peak or trough points of each test response parameter on the curve). As Figure 2 shown, Figure 2 is a schematic diagram of the first fundamental frequency region of the simulation method of the surface acoustic wave device provided by the embodiment of the present invention. In the figure, f1 is the resonance frequency point, f2 is the anti-resonance frequency point, the first center point is (f1 + f2) / 2. Taking the preset range as 200 MHz as an example, in addition to the resonance frequency point and the anti-resonance frequency point, the extreme points in the first fundamental frequency region also include the other 4 points (that is, f3~f6), then the first feature points include f1~f6, six feature points.

[0057] S32. Calculate a second center point according to the resonance frequency point and the anti-resonance frequency point in the simulation response parameters, and use the area of the second center point within a preset range as the second fundamental frequency region, and extract the extreme points in the second fundamental frequency region as the second feature points; it should be noted that the first feature points are the maximum and minimum values within the preset range, and the second feature points are the other extreme points except the first feature points.

[0058] S33. Calculate the error function according to the first feature points and the second feature points;

[0059] S34. Define the coefficient corresponding to the material parameters of the resonator as the fitting parameter, and perform iterative optimization on the fitting parameter according to the error function through the second preset algorithm to obtain the optimized fitting parameter; wherein, the material parameters include a piezoelectric substrate material and a metal electrode material, and the material parameters of the piezoelectric substrate material include elastic constant c, piezoelectric constant e, dielectric constant , density , and the material parameters of the metal electrode material include elastic constant c, density .

[0060] In an embodiment of the present invention, in step S34, the following relationship is satisfied between the fitting parameter and the material parameter:

[0061] ; (2)

[0062] Among them, represents the density fitting parameter, represents the elastic constant fitting parameter, represents the piezoelectric constant fitting parameter, represents the dielectric constant fitting parameter, represents the first imaginary fitting parameter, represents the second imaginary fitting parameter, represents an imaginary number.

[0063] In the embodiment of the present invention, the error function is defined as , and the error function satisfies the following relationship:

[0064] ; (3)

[0065] Among them, represents the amplitude error weight coefficient, represents the frequency error weight coefficient, represents the number of the resonators, represents the amplitude of the second characteristic point, represents the amplitude of the first characteristic point, represents the frequency of the second characteristic point, represents the frequency of the first characteristic point.

[0066] Specifically, the amplitude and frequency of the second characteristic point include the amplitudes and frequencies of all characteristic points within the second fundamental frequency region, and the amplitude and frequency of the first characteristic point include the amplitudes and frequencies of all characteristic points within the first fundamental frequency region. The difference between the amplitude and frequency of the first characteristic point and the amplitude and frequency of the second characteristic point is the error function. By automatically iterating and calculating, the result of the error function is reduced, and finally the optimized fitting parameters corresponding to the material parameters that meet the conditions are obtained.

[0067] S35. Optimize the accurate simulation model of the surface acoustic wave according to the optimized fitting parameters to obtain the optimized accurate simulation model of the surface acoustic wave. When the optimized accurate simulation model of the surface acoustic wave simulates the surface acoustic wave device to be simulated, it satisfies the relationship shown in formula (2).

[0068] S4. Use the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as the input of the optimized accurate simulation model of the surface acoustic wave device to perform simulation and obtain the simulation result.

[0069] In the embodiment of the present invention, the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated are used as the optimized accurate simulation model of the surface acoustic wave device, and the result is as Figures 3 - 4 shown, Figure 3It is a simulation test comparison diagram of the response parameters of the simulation method of the surface acoustic wave device provided by the embodiment of the present invention; Figure 4 It is a simulation test comparison diagram of the response parameters of the surface acoustic wave dual-mode device of the simulation method of the surface acoustic wave device provided by the embodiment of the present invention. It can be seen that when the optimized surface acoustic wave device precise simulation model proposed by the present invention is used for simulation, the accuracy of the simulation result is higher.

[0070] Compared with the prior art, the present invention obtains the test response parameters of the surface acoustic wave device; wherein, the surface acoustic wave device includes a plurality of resonators with different geometric design parameters; based on the first preset algorithm, a precise simulation model of the surface acoustic wave device is established, and the geometric design parameters corresponding to each resonator are used as the input of the precise simulation model of the surface acoustic wave device for calculation to obtain the simulation response parameters corresponding to each resonator; an error function is established according to the test response parameters and the simulation response parameters, and based on the second preset algorithm, the precise simulation model of the surface acoustic wave device is iteratively optimized according to the error function to obtain an optimized precise simulation model of the surface acoustic wave; the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated are used as the input of the optimized precise simulation model of the surface acoustic wave device for simulation to obtain the simulation result. The present invention can effectively reduce the simulation influence of the surface acoustic wave device caused by process errors and changes in the packaging test environment during the production process, improve the design efficiency of the surface acoustic wave device, and reduce the cost of repeated production and testing.

[0071] Embodiment 2

[0072] The embodiment of the present invention also provides a simulation system for a surface acoustic wave device. Please refer to Figure 5 , Figure 5 It is a structural schematic diagram of the simulation system 200 of the surface acoustic wave device provided by the embodiment of the present invention Figure 5 , which includes:

[0073] S201. A test module for obtaining the test response parameters of the surface acoustic wave device; wherein, the surface acoustic wave device includes a plurality of resonators with different geometric design parameters;

[0074] S202. A simulation parameter calculation module for establishing a precise simulation model of the surface acoustic wave device based on the first preset algorithm, and using the geometric design parameters corresponding to each of the resonators as the input of the precise simulation model of the surface acoustic wave device for calculation to obtain the simulation response parameters corresponding to each of the resonators;

[0075] S203. An iterative optimization module, configured to establish an error function based on the resonance frequency points and anti-resonance frequency points in the test response parameters and the resonance frequency points and anti-resonance frequency points in the simulation response parameters, and iteratively optimize the accurate simulation model of the surface acoustic wave device based on the second preset algorithm according to the error function to obtain an optimized accurate simulation model of the surface acoustic wave device;

[0076] S204. A simulation module, configured to use the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as the input of the optimized accurate simulation model of the surface acoustic wave device for simulation to obtain a simulation result.

[0077] The simulation system 200 of the surface acoustic wave device can implement the steps in the simulation method of the surface acoustic wave device in the above embodiments and can achieve the same technical effects. Refer to the description in the above embodiments, and details are not described herein again.

[0078] Embodiment III

[0079] The embodiment of the present invention further provides a computer device. Please refer to Figure 6 , Figure 6 which is a schematic structural diagram of the computer device provided by the embodiment of the present invention. The computer device 300 includes: a memory 302, a processor 301, and a simulation program of the surface acoustic wave device stored on the memory 302 and executable on the processor 301.

[0080] The processor 301 calls the simulation program of the surface acoustic wave device stored in the memory 302 to execute the steps in the simulation method of the surface acoustic wave device provided by the embodiment of the present invention. Please refer to Figure 1 , specifically including the following steps:

[0081] S1. Obtain the test response parameters of the surface acoustic wave device; wherein, the surface acoustic wave device includes a plurality of resonators with different geometric design parameters.

[0082] In the embodiment of the present invention, the test response parameters of the surface acoustic wave device are obtained by testing other surface acoustic wave devices under similar process conditions and similar test conditions. Similar process conditions refer to that the surface acoustic wave device has clearly defined process flows and parameters, has a determined application scenario, and usually belongs to a batch of chip flows. Similar test conditions refer to that during the test stage, all surface acoustic wave devices are tested under the same external environment and measurement equipment to obtain test results in a short time. The test response parameters include admittance parameters and scattering parameters, and the geometric design parameters include parameters such as finger pitch, metallization rate, and aperture.

[0083] S2. Establish an accurate simulation model of the surface acoustic wave device based on the first preset algorithm. Use the geometric design parameters corresponding to each resonator as the input of the accurate simulation model of the surface acoustic wave device for calculation, and obtain the simulation response parameters corresponding to each resonator.

[0084] In the embodiment of the present invention, the simulation response parameters include admittance parameters and simulation parameters. The first preset algorithm includes one or more of the finite element method, the finite element / boundary element method, and the hierarchical cascade algorithm. Of course, it is not limited to the above algorithms, and other algorithms are also feasible.

[0085] In the embodiment of the present invention, in step S2, the simulation response parameters are processed and calculated based on the following relationship (piezoelectric physical equation):

[0086] ; (1)

[0087] Wherein, represents the elastic constant, represents the piezoelectric constant, represents the density, represents the dielectric constant, represents the displacement ( is the second derivative), represents the electric field, represents the strain. 、 and are all expressions.

[0088] S3. Establish an error function based on the resonance frequency points and anti-resonance frequency points in the test response parameters and the resonance frequency points and anti-resonance frequency points in the simulation response parameters. Iteratively optimize the accurate simulation model of the surface acoustic wave device based on the second preset algorithm according to the error function to obtain an optimized accurate simulation model of the surface acoustic wave.

[0089] In the embodiment of the present invention, the second preset algorithm includes one or more of the genetic algorithm, the particle swarm optimization algorithm, and the simulated annealing algorithm. Of course, it is not limited to the above algorithms, and other algorithms are also feasible.

[0090] In the embodiment of the present invention, in step S3, it includes the following steps:

[0091] S31. Calculate the first center point according to the resonance frequency points and anti-resonance frequency points in the test response parameters, and use the area within the preset range of the first center point as the first fundamental frequency region. Extract the extreme points in the first fundamental frequency region as the first feature points (that is, select the obvious peak or trough points on the curve of each test response parameter). As Figure 2 shown, Figure 2 isFigure 2 It is a schematic diagram of the first fundamental frequency region of the simulation method for the surface acoustic wave device provided by the embodiment of the present invention. In the figure, f1 is the resonance frequency point, f2 is the anti-resonance frequency point, and the first center point is (f1 + f2) / 2. Taking the preset range of 200 MHz as an example, in the first fundamental frequency region, in addition to the resonance frequency point and the anti-resonance frequency point, the extreme points also include the other 4 points (i.e., f3~f6). Then the first characteristic points include f1~f6, a total of six characteristic points.

[0092] S32. Calculate the second center point according to the resonance frequency point and the anti-resonance frequency point in the simulation response parameters, and use the region within the preset range centered on the second center point as the second fundamental frequency region, and extract the extreme points in the second fundamental frequency region as the second characteristic points;

[0093] S33. Calculate the error function according to the first characteristic points and the second characteristic points;

[0094] S34. Define the coefficients corresponding to the material parameters of the resonator as fitting parameters, and iteratively optimize the fitting parameters according to the error function through the second preset algorithm to obtain optimized fitting parameters; wherein, the material parameters include the piezoelectric substrate material and the metal electrode material, and the material parameters of the piezoelectric substrate material include the elastic constant c, the piezoelectric constant e, the dielectric constant , density , and the material parameters of the metal electrode material include the elastic constant c, density .

[0095] In the embodiment of the present invention, in step S34, the following relationship is satisfied between the fitting parameters and the material parameters:

[0096] ; (2)

[0097] wherein, represents the density fitting parameter, represents the elastic constant fitting parameter, represents the piezoelectric constant fitting parameter, represents the dielectric constant fitting parameter, represents the first imaginary fitting parameter, represents the second imaginary fitting parameter, represents the imaginary number.

[0098] In the embodiment of the present invention, the error function is defined as , and the error function satisfies the following relationship:

[0099] ; (3)

[0100] wherein, represents the amplitude error weight coefficient, represents the frequency error weight coefficient, represents the number of the resonators, represents the amplitude of the second feature point, represents the amplitude of the first feature point, represents the frequency of the second feature point, represents the frequency of the first feature point.

[0101] Specifically, the amplitude and frequency of the second feature point include the amplitudes and frequencies of all feature points within the second fundamental frequency region, and the amplitude and frequency of the first feature point include the amplitudes and frequencies of all feature points within the first fundamental frequency region. The difference between the amplitude and frequency of the first feature point and those of the second feature point is the error function. By automatically iteratively calculating the result of reducing the error function, the optimized fitting parameters corresponding to the material parameters that meet the conditions are finally obtained.

[0102] S35. Optimize the accurate simulation model of the surface acoustic wave according to the optimized fitting parameters to obtain the optimized accurate simulation model of the surface acoustic wave. When the optimized accurate simulation model of the surface acoustic wave simulates the surface acoustic wave device to be simulated, it satisfies the relationship shown in formula (2).

[0103] S4. Use the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as the input of the optimized accurate simulation model of the surface acoustic wave device for simulation to obtain the simulation results.

[0104] In the embodiment of the present invention, the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated are used as the optimized accurate simulation model of the surface acoustic wave device, and the result is as Figures 3 - 4 shown, Figure 3 It is a simulation test comparison diagram of the response parameters of the simulation method of the surface acoustic wave device provided by the embodiment of the present invention; Figure 4 It is a simulation test comparison diagram of the response parameters of the surface acoustic wave dual-mode device of the simulation method of the surface acoustic wave device provided by the embodiment of the present invention. It can be seen that when the simulation is performed through the optimized accurate simulation model of the surface acoustic wave device proposed by the present invention, the accuracy of the simulation result is higher.

[0105] The computer device 300 provided by the embodiment of the present invention can implement the steps in the simulation method of the surface acoustic wave device in the above embodiment and can achieve the same technical effects. Refer to the description in the above embodiment, and details are not described here again.

[0106] Embodiment Four

[0107] An embodiment of the present invention further provides a computer-readable storage medium, on which a simulation program of a surface acoustic wave device is stored. When the simulation program of the surface acoustic wave device is executed by a processor, each process and step in the simulation method of the surface acoustic wave device provided by the embodiment of the present invention is implemented, and the same technical effects can be achieved. To avoid repetition, it will not be described in detail here.

[0108] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0109] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or device including the element.

[0110] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods in the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in various embodiments of the present invention.

[0111] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. What is disclosed is only the preferred embodiments of the present invention. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many equivalent changes in form without departing from the spirit and scope protected by the claims of the present invention, and all of them belong to the protection scope of the present invention.

Claims

1. A method for simulating a surface acoustic wave device, characterized in that: The simulation method comprises the following steps: S1. Obtaining test response parameters of a surface acoustic wave device; wherein the surface acoustic wave device includes a plurality of resonators with different geometric design parameters; S2, establishing a precise simulation model of a surface acoustic wave device based on a first preset algorithm, taking the geometric design parameters corresponding to each of the resonators as inputs of the precise simulation model of the surface acoustic wave device for calculation, and obtaining simulation response parameters corresponding to each of the resonators; S3, establishing an error function according to the resonant frequency point and the anti-resonant frequency point in the test response parameter and the resonant frequency point and the anti-resonant frequency point in the simulation response parameter, and iteratively optimizing the precise simulation model of the surface acoustic wave device according to the error function based on a second preset algorithm to obtain an optimized precise simulation model of the surface acoustic wave device; S4, using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as input of the optimized surface acoustic wave device accurate simulation model to perform simulation and obtain simulation results; Step S3 includes the following steps: S31, calculating a first center point according to the resonant frequency point and the anti-resonant frequency point in the test response parameter, taking an area within a preset range of the first center point as a first fundamental frequency area, and extracting an extreme value point in the first fundamental frequency area as a first feature point; S32, calculating a second center point according to the resonant frequency point and the anti-resonant frequency point in the simulation response parameter, taking the area of ​​the second center point within a preset range as a second fundamental frequency area, and extracting an extreme value point in the second fundamental frequency area as a second feature point; S33, calculating the error function according to the first feature point and the second feature point; S34, defining coefficients corresponding to the material parameters of the resonator as fitting parameters, and iteratively optimizing the fitting parameters according to the error function using the second preset algorithm to obtain optimized fitting parameters; wherein the material parameters include piezoelectric substrate material and metal electrode material; S35, optimizing the surface acoustic wave precise simulation model according to the optimized fitting parameters to obtain the optimized surface acoustic wave device precise simulation model; The simulation response parameters are processed and calculated based on the following relationship: ； in, represents the elastic constant, represents the piezoelectric constant, represents density, represents the dielectric constant, represents displacement, represents the electric field, Indicates strain.

2. The method for simulating a surface acoustic wave device according to claim 1, wherein: In step S34, the fitting parameters and the material parameters satisfy the following relationship: ； in, represents the density fitting parameter, represents the elastic constant fitting parameter, represents the piezoelectric constant fitting parameter, represents the dielectric constant fitting parameter, represents the first imaginary fitting parameter, represents the second imaginary fitting parameter, Represents an imaginary number.

3. The method for simulating a surface acoustic wave device according to claim 2, wherein: The error function is defined as , the error function satisfies the following relationship: ； in, represents the amplitude error weight coefficient, represents the frequency error weight coefficient, represents the number of the resonators, represents the amplitude of the second feature point, represents the amplitude of the first feature point, represents the frequency of the second feature point, Represents the frequency of the first feature point.

4. The method for simulating a surface acoustic wave device according to claim 1, wherein: The first preset algorithm includes one or more of a finite element method, a finite element / boundary element method, and a hierarchical cascade algorithm.

5. The method for simulating a surface acoustic wave device according to claim 1, wherein: The second preset algorithm includes one or more of a genetic algorithm, a particle swarm optimization algorithm, and a simulated annealing algorithm.

6. A simulation system for a surface acoustic wave device, characterized in that: include: A test module, used to obtain test response parameters of a surface acoustic wave device; wherein the surface acoustic wave device includes a plurality of resonators with different geometric design parameters; A simulation parameter calculation module is used to establish a precise simulation model of a surface acoustic wave device based on a first preset algorithm, and to calculate the geometric design parameters corresponding to each of the resonators as inputs of the precise simulation model of the surface acoustic wave device to obtain simulation response parameters corresponding to each of the resonators; wherein the simulation response parameters are processed and calculated based on the following relationship: ； in, represents the elastic constant, represents the piezoelectric constant, represents density, represents the dielectric constant, represents displacement, represents the electric field, Indicates strain; an iterative optimization module, configured to establish an error function according to the resonant frequency point and the anti-resonant frequency point in the test response parameter and the resonant frequency point and the anti-resonant frequency point in the simulation response parameter, and iteratively optimize the precise simulation model of the surface acoustic wave device according to the error function based on a second preset algorithm to obtain an optimized precise simulation model of the surface acoustic wave device; The iterative optimization module is also used for: Calculate a first center point according to the resonant frequency point and the anti-resonant frequency point in the test response parameter, take the area within a preset range of the first center point as a first fundamental frequency area, and extract the extreme value point in the first fundamental frequency area as a first feature point; Calculate a second center point according to the resonant frequency point and the anti-resonant frequency point in the simulation response parameter, take the area within the preset range of the second center point as the second fundamental frequency area, and extract the extreme value point in the second fundamental frequency area as the second feature point; Calculating the error function according to the first feature point and the second feature point; Defining coefficients corresponding to the material parameters of the resonator as fitting parameters, and iteratively optimizing the fitting parameters according to the error function using the second preset algorithm to obtain optimized fitting parameters; wherein the material parameters include piezoelectric substrate material and metal electrode material; Optimizing the surface acoustic wave precise simulation model according to the optimized fitting parameters to obtain the optimized surface acoustic wave device precise simulation model; The simulation module is used to simulate the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as input of the precise simulation model of the optimized surface acoustic wave device to obtain simulation results.

7. A computer device, characterized in that: include: A memory, a processor, and a simulation program for a surface acoustic wave device stored in the memory and executable on the processor, wherein the processor implements the steps of the simulation method for a surface acoustic wave device as described in any one of claims 1 to 5 when executing the simulation program for the surface acoustic wave device.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a simulation program for a surface acoustic wave device, and when the simulation program for a surface acoustic wave device is executed by a processor, the steps in the simulation method for a surface acoustic wave device as claimed in any one of claims 1 to 5 are implemented.

Images