Simulation method and system of surface acoustic wave device and related equipment

Abstract

The invention is suitable for the technical field of communication, and particularly relates to a simulation method and system of a surface acoustic wave device and related equipment. The method comprises the following steps: acquiring test response parameters of the surface acoustic wave device; based on a first preset algorithm, establishing an accurate simulation model of the surface acoustic wave device, and calculating by taking the geometric design parameter corresponding to each resonator as the input of the accurate simulation model of the surface acoustic wave device to obtain a simulation response parameter corresponding to each resonator; performing iterative optimization on the accurate simulation model of the surface acoustic wave device according to the error function based on a second preset algorithm to obtain an optimized accurate simulation model of the surface acoustic wave; and a simulation result is obtained by optimizing the surface acoustic wave accurate simulation model. Compared with the prior art, the method has the advantages that the simulation influence of the surface acoustic wave device caused by process errors and packaging test environment changes in the production process can be effectively reduced, the design efficiency of the surface acoustic wave device is improved, and the cost of repeated production tests is reduced.

Description

Technical Field

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

[0002] Surface acoustic wave filters are an important component of the RF front end of the communication industry. They are widely used because of their excellent frequency selectivity, low power consumption, and small size. Simulation technology plays a vital role in the design and manufacture of surface acoustic wave filters. Accurate simulation can help designers optimize the performance of the filter. Accurate simulation models of surface acoustic wave filters include finite element analysis (FEM), finite element / boundary element method (FEM / BEM), hierarchical cascade method (HCT), etc. These models are based on the basic physical laws of the system and combine mechanics, electricity and other multi-physical fields to describe the behavior of the system. By selecting appropriate material parameters, adjusting the geometric structure of the device, including finger width, finger spacing, number of fingers, etc., and setting boundary conditions, the response parameters of the surface acoustic wave device can be simulated and calculated 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 literatures have verified and published the material parameters obtained under experimental conditions, these parameters have not been calculated very accurately in practical applications. Especially in high-frequency applications, there is a large deviation between simulation and test results, which limits their application to a certain extent. The reasons for the difference between simulation and test include: process errors caused by the device during the tape-out production process, slight differences from the actual situation caused by the simplification of device simulation conditions, and performance impact caused by changes in packaging and test environment.

[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 surface acoustic wave device simulation method, system and related equipment, aiming to improve the simulation cost and efficiency of the surface acoustic wave device.

[0006] In a first aspect, the present invention provides a method for simulating a surface acoustic wave device, the method comprising 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; S4. Using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as inputs of the optimized surface acoustic wave device precise simulation model to perform simulation and obtain simulation results.

[0007] Preferably, 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. Optimize the surface acoustic wave precise simulation model according to the optimized fitting parameters to obtain the optimized surface acoustic wave precise simulation model.

[0008] Preferably, in step S2, the simulation response parameter is 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.

[0009] Preferably, in step S34, the fitting parameter and the material parameter 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.

[0010] Preferably, 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, Indicates the frequency of the first feature point.

[0011] Preferably, the first preset algorithm includes one or more of a finite element method, a finite element / boundary element method and a hierarchical cascade algorithm.

[0012] Preferably, the second preset algorithm includes one or more of a genetic algorithm, a particle swarm optimization algorithm and a simulated annealing algorithm.

[0013] In a second aspect, the present invention further provides a simulation system for a surface acoustic wave device, comprising: 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, 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; an iterative optimization module, configured to establish an error function according to the test response parameter and the simulation response parameter, and iteratively optimize the surface acoustic wave device precise simulation model according to the error function based on a second preset algorithm to obtain an optimized surface acoustic wave 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.

[0014] In a third aspect, the present invention further provides a computer device comprising: 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 in the simulation method for a surface acoustic wave device as described in any one of the above embodiments when executing the simulation program for the surface acoustic wave device.

[0015] In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a simulation program for a surface acoustic wave device is stored. When the simulation program for the surface acoustic wave device is executed by a processor, the steps in the simulation method for the surface acoustic wave device as described in any one of the above embodiments are implemented.

[0016] 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; establishes a precise simulation model of the surface acoustic wave device based on a first preset algorithm, calculates the geometric design parameters corresponding to each resonator as the input of the precise simulation model of the surface acoustic wave device, and obtains the simulation response parameters corresponding to each resonator; establishes an error function according to the test response parameters and the simulation response parameters, iteratively optimizes the precise simulation model of the surface acoustic wave device according to the error function based on a second preset algorithm, and obtains an optimized precise simulation model of the surface acoustic wave; and simulates the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as the input of the precise simulation model of the optimized surface acoustic wave device to obtain a simulation result. The present invention can effectively reduce the simulation impact 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be described in detail below in conjunction with the accompanying drawings. The above and other aspects of the present invention will become clearer and easier to understand through the detailed description made in conjunction with the following drawings. In the accompanying drawings: Figure 1 It is a flowchart of a simulation method for a surface acoustic wave device provided by an embodiment of the present invention; Figure 2 It 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; 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; Figure 4 It is a simulation test comparison diagram of response parameters of a surface acoustic wave dual-mode device according to a simulation method for a surface acoustic wave device provided by an embodiment of the present invention; Figure 5It is a structural schematic diagram of a simulation system for a surface acoustic wave device provided by an embodiment of the present invention; Figure 6 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is 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 intended to limit the present invention.

[0019] Embodiment 1 Please refer to Figure 1-Figure 4 The present invention provides a method for simulating a surface acoustic wave device, the method for simulating a surface acoustic wave device comprising 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.

[0020] In an 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 surface acoustic wave devices having clearly defined process flows and parameters, having certain application scenarios, and usually belonging to a batch of tape-outs. Similar test conditions refer to that during the test phase, all surface acoustic wave devices are tested in the same external environment and with the same measuring equipment in a short time to obtain test results. 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.

[0021] S2. Establishing a precise simulation model of a surface acoustic wave device based on a first preset algorithm, taking 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.

[0022] In an embodiment of the present invention, the simulation response parameters, admittance parameters and simulation parameters, the first preset algorithm includes one or more of finite element method, finite element / boundary element method and hierarchical cascade algorithm, of course, it is not limited to the above algorithms, other algorithms are also feasible.

[0023] In the embodiment of the present invention, in step S2, the simulation response parameter is processed and calculated based on the following relationship (piezoelectric physical equation): ; (1) in, represents the elastic constant, represents the piezoelectric constant, represents density, represents the dielectric constant, Represents displacement ( is the second-order derivative), represents the electric field, Indicates strain. , as well as All are expressions.

[0024] S3. Establish an error function according to the resonant frequency points and anti-resonant frequency points in the test response parameters and the resonant frequency points and anti-resonant frequency points in the simulation response parameters, 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. 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, but is certainly not limited to the above algorithms, and other algorithms are also feasible.

[0025] In the embodiment of the present invention, 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, and taking the area within the preset range of the first center point as the first fundamental frequency area, extracting the extreme value point in the first fundamental frequency area as the first feature point (i.e. selecting the point where each test response parameter has an obvious peak or trough on the curve). Figure 2 As shown, Figure 2 It is a schematic diagram of the first fundamental frequency region of the simulation method of the surface acoustic wave device provided by an embodiment of the present invention. In the figure, f1 is the resonant frequency point, f2 is the anti-resonant frequency point, the first center point is (f1+f2) / 2, and taking the preset range of 200MHz as an example, the extreme points in the first fundamental frequency region include the remaining 4 points (i.e., f3~f6) in addition to the resonant frequency point and the anti-resonant frequency point, then the first characteristic points include f1~f6, six characteristic points.

[0026] S32. Calculate a second center point based on the resonant frequency point and the anti-resonant 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 area, and extract the extreme points in the second fundamental frequency area as second feature points; it should be noted that the first feature point is the maximum and minimum values ​​within the preset range, and the second feature point is the extreme points other than the first feature point.

[0027] S33, calculating the error function according to the first feature point and the second feature point; S34, defining the coefficients corresponding to the material parameters of the resonator as fitting parameters, and iteratively optimizing the fitting parameters according to the error function through the second preset algorithm to obtain optimized fitting parameters; wherein the material parameters include piezoelectric substrate material and metal electrode material, and the material parameters of the piezoelectric substrate material include elastic constant c, piezoelectric constant e, dielectric constant ,density The material parameters of metal electrode materials include elastic constant c, density .

[0028] In the embodiment of the present invention, in step S34, the fitting parameter and the material parameter satisfy the following relationship: ; (2) 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.

[0029] In the embodiment of the present invention, the error function is defined as , the error function satisfies the following relationship: ; (3) 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, Indicates the frequency of the first feature point.

[0030] Specifically, the amplitude and frequency of the second characteristic point include the amplitude and frequency of all characteristic points in the second baseband region, and the amplitude and frequency of the first characteristic point include the amplitude and frequency of all characteristic points in the first baseband 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. The result of the error function is reduced by automatic iterative calculation, and finally the optimized fitting parameters corresponding to the material parameters that meet the conditions are optimized.

[0031] S35, optimizing the surface acoustic wave precise simulation model according to the optimized fitting parameters to obtain the optimized surface acoustic wave precise simulation model. When the optimized surface acoustic wave precise simulation model simulates the surface acoustic wave device to be simulated, the relationship shown in formula (2) is satisfied.

[0032] S4. Using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as inputs of the optimized surface acoustic wave device precise simulation model to perform simulation and obtain simulation results.

[0033] 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 precise simulation model of the optimized surface acoustic wave device. Figure 3-Figure 4 As shown, 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; 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 by the optimized surface acoustic wave device accurate simulation model proposed by the present invention, the simulation result has a higher accuracy.

[0034] 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; establishes a precise simulation model of the surface acoustic wave device based on a first preset algorithm, calculates the geometric design parameters corresponding to each resonator as the input of the precise simulation model of the surface acoustic wave device, and obtains the simulation response parameters corresponding to each resonator; establishes an error function according to the test response parameters and the simulation response parameters, iteratively optimizes the precise simulation model of the surface acoustic wave device according to the error function based on a second preset algorithm, and obtains an optimized precise simulation model of the surface acoustic wave; and simulates the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as the input of the precise simulation model of the optimized surface acoustic wave device to obtain a simulation result. The present invention can effectively reduce the simulation impact 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.

[0035] Embodiment 2 The embodiment of the present invention also provides a simulation system for a surface acoustic wave device, please refer to Figure 5 , Figure 5 FIG. 2 is a schematic diagram of a simulation system 200 for a surface acoustic wave device according to an embodiment of the present invention. Figure 5 , which includes: S201, a test module, used to obtain a test response parameter of a surface acoustic wave device; wherein the surface acoustic wave device includes a plurality of resonators with different geometric design parameters; S202, a simulation parameter calculation module, 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; S203, an iterative optimization module, used 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; S204, a simulation module, used for performing simulation 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 precise simulation model to obtain simulation results.

[0036] The surface acoustic wave device simulation system 200 can implement the steps in the surface acoustic wave device simulation method in the above embodiment, and can achieve the same technical effects. Please refer to the description in the above embodiment, which will not be repeated here.

[0037] Embodiment 3 The embodiment of the present invention also provides a computer device, please refer to Figure 6 , Figure 6 300 is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. The computer device 300 includes: a memory 302 , a processor 301 , and a simulation program of a surface acoustic wave device stored in the memory 302 and executable on the processor 301 .

[0038] The processor 301 calls the simulation program of the surface acoustic wave device stored in the memory 302 to execute the steps of the simulation method of the surface acoustic wave device provided by the embodiment of the present invention. Figure 1 , specifically including 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.

[0039] In an 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 surface acoustic wave devices having clearly defined process flows and parameters, having certain application scenarios, and usually belonging to a batch of tape-outs. Similar test conditions refer to that during the test phase, all surface acoustic wave devices are tested in the same external environment and with the same measuring equipment in a short time to obtain test results. 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.

[0040] S2. Establishing a precise simulation model of a surface acoustic wave device based on a first preset algorithm, taking 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.

[0041] In an embodiment of the present invention, the simulation response parameters, admittance parameters and simulation parameters, the first preset algorithm includes one or more of finite element method, finite element / boundary element method and hierarchical cascade algorithm, of course, it is not limited to the above algorithms, other algorithms are also feasible.

[0042] In the embodiment of the present invention, in step S2, the simulation response parameter is processed and calculated based on the following relationship (piezoelectric physical equation): ; (1) in, represents the elastic constant, represents the piezoelectric constant, represents density, represents the dielectric constant, Represents displacement ( is the second-order derivative), represents the electric field, Indicates strain. , as well as All are expressions.

[0043] S3. Establish an error function according to the resonant frequency points and anti-resonant frequency points in the test response parameters and the resonant frequency points and anti-resonant frequency points in the simulation response parameters, 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. 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, but is certainly not limited to the above algorithms, and other algorithms are also feasible.

[0044] In the embodiment of the present invention, 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, and taking the area within the preset range of the first center point as the first fundamental frequency area, extracting the extreme value point in the first fundamental frequency area as the first feature point (i.e. selecting the point where each test response parameter has an obvious peak or trough on the curve). Figure 2 As shown, Figure 2 for Figure 2 It is a schematic diagram of the first fundamental frequency region of the simulation method of the surface acoustic wave device provided by an embodiment of the present invention. In the figure, f1 is the resonant frequency point, f2 is the anti-resonant frequency point, the first center point is (f1+f2) / 2, and taking the preset range of 200MHz as an example, the extreme points in the first fundamental frequency region include the remaining 4 points (i.e., f3~f6) in addition to the resonant frequency point and the anti-resonant frequency point, then the first characteristic points include f1~f6, six characteristic points.

[0045] 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 the coefficients corresponding to the material parameters of the resonator as fitting parameters, and iteratively optimizing the fitting parameters according to the error function through the second preset algorithm to obtain optimized fitting parameters; wherein the material parameters include piezoelectric substrate material and metal electrode material, and the material parameters of the piezoelectric substrate material include elastic constant c, piezoelectric constant e, dielectric constant ,density The material parameters of metal electrode materials include elastic constant c, density .

[0046] In the embodiment of the present invention, in step S34, the fitting parameter and the material parameter satisfy the following relationship: ; (2) 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.

[0047] In the embodiment of the present invention, the error function is defined as , the error function satisfies the following relationship: ; (3) 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, Indicates the frequency of the first feature point.

[0048] Specifically, the amplitude and frequency of the second characteristic point include the amplitude and frequency of all characteristic points in the second baseband region, and the amplitude and frequency of the first characteristic point include the amplitude and frequency of all characteristic points in the first baseband 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. The result of the error function is reduced by automatic iterative calculation, and finally the optimized fitting parameters corresponding to the material parameters that meet the conditions are optimized.

[0049] S35, optimizing the surface acoustic wave precise simulation model according to the optimized fitting parameters to obtain the optimized surface acoustic wave precise simulation model. When the optimized surface acoustic wave precise simulation model simulates the surface acoustic wave device to be simulated, the relationship shown in formula (2) is satisfied.

[0050] S4. Using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as inputs of the optimized surface acoustic wave device precise simulation model to perform simulation and obtain simulation results.

[0051] 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 precise simulation model of the optimized surface acoustic wave device. Figure 3-Figure 4 As shown, 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; 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 by the optimized surface acoustic wave device accurate simulation model proposed by the present invention, the simulation result has a higher accuracy.

[0052] The computer device 300 provided in 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 effect. Please refer to the description in the above embodiment and will not be repeated here.

[0053] Embodiment 4 An embodiment of the present invention further provides a computer-readable storage medium, on which a simulation program for a surface acoustic wave device is stored. When the simulation program for the surface acoustic wave device is executed by a processor, the various processes and steps in the simulation method for the surface acoustic wave device provided in the embodiment of the present invention are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0054] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0055] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0056] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling 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 each embodiment of the present invention.

[0057] The embodiments of the present invention are described above in conjunction with the accompanying drawings. What is disclosed is only the preferred embodiment of the present invention. However, the present invention is not limited to the above-mentioned specific implementation manner. The above-mentioned specific implementation manner is only illustrative rather than restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms and equivalent changes without departing from the scope of protection of the purpose of the present invention and the claims, all of which are within the protection 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; S4. Using the geometric design parameters corresponding to each resonator in the surface acoustic wave device to be simulated as inputs of the optimized surface acoustic wave device precise simulation model to perform simulation and obtain simulation results.

2. The method for simulating a surface acoustic wave device according to claim 1, wherein: 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. Optimize the surface acoustic wave precise simulation model according to the optimized fitting parameters to obtain the optimized surface acoustic wave precise simulation model.

3. The method for simulating a surface acoustic wave device according to claim 2, wherein: In step S2, 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.

4. The method for simulating a surface acoustic wave device according to claim 3, 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.

5. The method for simulating a surface acoustic wave device according to claim 4, characterized in that: 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.

6. 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.

7. 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.

8. 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, 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; 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; 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.

9. 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 in the simulation method for a surface acoustic wave device as described in any one of claims 1 to 7 when executing the simulation program for the surface acoustic wave device.

10. 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 7 are implemented.

Images