Simulation method, device, electronic device and storage medium of surface acoustic wave device

Abstract

The present invention relates to the field of surface acoustic wave simulation technology, and provides a simulation method, device, electronic device and storage medium for a surface acoustic wave device. The simulation method specifically uses a frequency domain finite element algorithm to segment and calculate the device. In the specific calculation process, the displacement on the preset surface is retained by redesigning the simulation process and re-dividing the degrees of freedom in the matrix equation. Therefore, based on the displacement on the preset surface, the wave number domain vibration mode distribution result on the preset surface can be calculated, and the admittance of the device can be calculated by determining the charge on the interdigital electrodes, and finally a frequency response curve is drawn. The simulation process is simple and has high solution efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of surface acoustic wave simulation, and in particular to a simulation method, device, electronic equipment and storage medium for a surface acoustic wave device. Background Art

[0002] Generally, the number of degrees of freedom (millions of degrees of freedom) contained in a full-size surface acoustic wave (SAW) device model far exceeds the memory and computing power of an ordinary computer. Therefore, a slice model with additional periodic boundary conditions is usually used to replace the full-size finite element method (FEM) model. Specifically, the full-size SAW device can be divided into the same unit blocks and matrix cascade elimination can be performed. The admittance response of the surface acoustic wave resonator can be quickly solved based on the longitudinal slice model of the surface acoustic wave resonator. However, in order to pursue simulation efficiency, a large number of internal potential degrees of freedom will be eliminated during the simulation calculation process to solve the admittance of the SAW device. In fact, the vibration mode of the device is also an important indicator for evaluating the device. Sampling the existing simulation algorithm to simultaneously determine the vibration mode of the device requires a very cumbersome inverse solution process. Therefore, there is an urgent need for a method that can quickly and accurately solve the admittance and vibration mode of the SAW device. Summary of the invention

[0003] In order to solve the problems of the prior art, the embodiments of the present application provide a method, device, electronic device and storage medium for simulating a surface acoustic wave device. The technical solution is as follows:

[0004] In one aspect, a method for simulating a surface acoustic wave device is provided, comprising:

[0005] Segmenting and identifying the surface acoustic wave device model to obtain a core unit model corresponding to the multiple unit models;

[0006] Based on the preset frequency, the core unit model is analyzed using the finite element algorithm to obtain the system matrix equation of the core unit model; the system matrix equation is used to characterize the relationship between the system matrix, the degree of freedom vector on the preset side periodic boundary condition, the remaining degree of freedom vector and the load vector on the preset side periodic boundary condition, and other load vectors; the remaining degree of freedom vector represents the system degree of freedom vector except the degree of freedom on the preset side periodic boundary condition;

[0007] Classify and rearrange the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model; the initial target matrix equation is used to characterize the relationship between the rearranged system matrix, the displacement vector on the preset surface, the degree of freedom vector on the cascade surface, the electric potential of the interdigital electrode and the load vector on the preset surface, the load vector on the cascade surface, and the charge of the interdigital electrode;

[0008] Based on the initial target matrix equation of the core unit model, each unit model is cascaded to obtain the target matrix equation of the surface acoustic wave device model;

[0009] Determine the displacement vector on the preset surface and the charge amount of the interdigital electrodes based on the target matrix equation of the surface acoustic wave device model;

[0010] The wave number domain vibration mode distribution result and admittance of the surface acoustic wave device model are determined based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes.

[0011] In another aspect, a simulation device for a surface acoustic wave device is provided, the device comprising:

[0012] A segmentation module is used to segment and identify the surface acoustic wave device model to obtain a core unit model corresponding to multiple unit models;

[0013] The analytical module is used to analyze the core unit model based on the preset frequency using the finite element algorithm to obtain the system matrix equation of the core unit model; the system matrix equation is used to characterize the relationship between the system matrix, the degree of freedom vector on the preset side periodic boundary condition, the remaining degree of freedom vector and the load vector on the preset side periodic boundary condition, and other load vectors; the remaining degree of freedom vector represents the system degree of freedom vector except the degree of freedom on the preset side periodic boundary condition;

[0014] A classification and rearrangement module is used to classify and rearrange the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model; the initial target matrix equation is used to characterize the relationship between the processed system matrix, the displacement vector on the preset surface, the degree of freedom vector on the cascade surface, the potential of the interdigital electrode and the load vector on the preset surface, the load vector on the cascade surface, and the charge of the interdigital electrode;

[0015] A cascade processing module, used for performing cascade processing on each unit model based on the initial target matrix equation of the core unit model to obtain a target matrix equation of the surface acoustic wave device model;

[0016] A first determination module is used to determine the displacement vector on the preset surface and the charge amount of the interdigital electrodes based on the target matrix equation of the surface acoustic wave device model;

[0017] The second determination module is used to determine the wave number domain vibration mode distribution result and admittance of the surface acoustic wave device model based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes.

[0018] On the other hand, an electronic device is provided, which includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the simulation method of the surface acoustic wave device in any of the above aspects.

[0019] On the other hand, a computer-readable storage medium is provided, in which at least one instruction or at least one program is stored, and the at least one instruction or the at least one program is loaded and executed by a processor to implement a simulation method of a surface acoustic wave device as described in any of the above aspects.

[0020] The embodiment of the present application redesigns the simulation process and re-divides the degrees of freedom in the matrix equation, retaining the displacement on the preset surface, so that the wave number domain vibration mode distribution result on the preset surface can be calculated based on the displacement on the preset surface, and the admittance of the device can be calculated by determining the charge on the interdigital electrodes, and finally the frequency response curve is drawn. The simulation process is simple and has high solution efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 is a schematic structural diagram of a surface acoustic wave resonator provided in an embodiment of the present application;

[0023] Figure 2 is a schematic structural diagram of a surface electrode of a surface acoustic wave resonator provided in an embodiment of the present application;

[0024] Figure 3 It is a schematic diagram of an implementation environment provided by an embodiment of the present application;

[0025] Figure 4 It is a flow chart of a simulation method of a surface acoustic wave device provided in an embodiment of the present application;

[0026] Figure 5 It is a flow chart of a system matrix equation for determining a core unit model provided in an embodiment of the present application;

[0027] Figure 6 It is a structural schematic diagram of a unit model provided in an embodiment of the present application;

[0028] Figure 7 It is a flow chart of another system matrix equation for determining a core unit model provided in an embodiment of the present application;

[0029] Figure 8 It is a schematic diagram of a process of cascading two adjacent unit models provided in an embodiment of the present application;

[0030] Fig. 9 is a schematic structural diagram of a cascaded surface acoustic wave resonator provided in an embodiment of the present application;

[0031] Fig.10 It is a schematic diagram of a spatial domain vibration mode provided in an embodiment of the present application;

[0032] Fig.11 It is a wave number domain vibration schematic diagram provided in an embodiment of the present application;

[0033] Fig.12 It is a structural block diagram of a simulation device for a surface acoustic wave device provided in an embodiment of the present application;

[0034] Fig.13 It is a hardware structure block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] It is understandable that in the specific implementation of this application, related data such as user information is involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0038] The terms involved in the embodiments of the present application are explained below.

[0039] Surface acoustic wave device: also known as surface acoustic wave resonator, the full name of which is surface acoustic wave, or SAW for short; the general structure is as follows Figure 1 As shown, it includes a supporting substrate, a piezoelectric film and a surface electrode arranged from bottom to top. Figure 2 As shown in the figure, the surface electrodes can be generally divided into two-side reflective gratings and interdigital transducers according to their geometric structure and function, wherein the interdigital transducer (IDT) is composed of two groups of interdigital electrodes that cross each other, an electrode array with a period of the working wavelength of the SAW device (respectively marked as the first interdigital electrode and the second interdigital electrode), and a bus bar that provides electrical connection.

[0040] Interdigital electrode: an important component of the interdigital transducer, see Figure 2 , specifically including a first interdigitated electrode and a second interdigitated electrode.

[0041] Longitudinal Slice Model: See Figure 2 The unit model obtained by slicing the device along the direction perpendicular to the interdigital electrodes is called the longitudinal slice model. Figure 2 The width types shown can be divided into three types of longitudinal slice models, corresponding to the width W G , W A , W B .

[0042] Cross-section model: see Figure 2 The unit model obtained by slicing the device along a direction parallel to the interdigital electrodes is called a transverse slicing model. The transverse slicing model can be a unit model including a pair of interdigital electrodes or a single interdigital electrode.

[0043] See also Figure 3, which is a schematic diagram of an implementation environment provided by an embodiment of the present application, the implementation environment includes a terminal 30 and a simulation module 301 located on the terminal. The simulation module 301 implements the simulation process of the surface acoustic wave device, such as segmenting the surface acoustic wave device model, constructing the system matrix equation, and re-dividing the degrees of freedom in the matrix equation to retain the displacement on the preset surface and the load of the interdigital electrode, thereby simulating the wave number domain vibration mode distribution result on the preset surface and the admittance of the device.

[0044] The terminal 110 includes but is not limited to mobile phones, computers, intelligent voice interaction devices, smart home appliances, vehicle terminals, aircraft, etc. The terminal 110 is installed with client software such as an application (Application, referred to as App) with content display function, which can be an independent application or a subprogram in the application.

[0045] It should be noted that the server involved in the embodiments of the present application can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network) and big data and artificial intelligence platforms.

[0046] See also Figure 4 , which is a schematic flow chart of a simulation method for a surface acoustic wave device provided in an embodiment of the present application, which method can be applied to Figure 3 In the simulation module in. It should be noted that this specification provides method operation steps as described in the embodiments or flow charts, but more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in the embodiments is only one way of executing the steps among many orders, and does not represent the only order of execution. When the actual system or product is executed, it can be executed in sequence or in parallel (for example, in a parallel processor or multi-threaded processing environment) according to the method shown in the embodiments or drawings. Specifically, Figure 4 As shown, the method may include:

[0047] S401: Segment and identify the surface acoustic wave device model to obtain a core unit model corresponding to the multiple unit models.

[0048] Since the number of degrees of freedom (millions of degrees of freedom) contained in a full-size SAW device model far exceeds the memory and computing power of an ordinary PC, a slice model with additional periodic boundary conditions is usually used to replace the full-size FEM model. In an exemplary embodiment, step S401 may include: constructing a surface acoustic wave device model; segmenting the surface acoustic wave device model based on a preset transverse slice model segmentation method or a longitudinal slice model segmentation method to obtain multiple unit models; identifying and classifying multiple unit models to obtain a core unit model. Optionally, a structure such as Figure 1 and Figure 2 The structure of the surface electrode of the surface acoustic wave device model is not limited to the above Figure 2 The structure shown.

[0049] In a feasible implementation, the above-mentioned identification and classification of multiple unit models to obtain a core unit model can be specifically explained as: classifying and identifying multiple unit models to obtain multiple unit model sets; taking any unit model in each unit model set as a core unit model.

[0050] In this embodiment, according to the adopted slicing method, such as the horizontal slicing model slicing method or the vertical slicing model slicing method, the obtained multiple unit models are different, see Figure 2 , if the horizontal slice model is sliced, multiple horizontal slice models can be obtained, and each horizontal slice model is further sliced, multiple unit models of each horizontal slice model can be obtained. In the processing process, multiple unit models can be first regarded as a whole set and classified into multiple subsets. The unit model in each subset is a repeated unit model, that is, it corresponds to a core unit module, so that the number of core unit models corresponding to each horizontal slice model can be determined; therefore, it is only necessary to calculate the matrix equation of each core unit model in the future. For a slice model, as long as the number, type and arrangement order of the core unit models it contains are known, the entire slice model can be cascaded. Generally, in the simulation process, in order to improve the simulation efficiency, in the slicing process, it is necessary to try to slice according to the core unit models that contain as few as possible, and the types of models for subsequent simulation calculations will also be fewer. Similarly, refer to Figure 2If the longitudinal slice model is sliced ​​in the same way, multiple longitudinal slice models can be obtained. If each longitudinal slice model is further sliced, multiple unit models of each longitudinal slice model can be obtained. The subsequent classification process can be the same as the unit model of the transverse slice model. By further comparing the transverse slice model and the longitudinal slice model, it can be found that the electrode structure features of the IDT region of the longitudinal slice model are relatively few, and a unit model cut out can be a unit model with only one interdigitated electrode structure, which is convenient for subsequent calculations. The longitudinal slice model will be used as an example for explanation below.

[0051] S403: Based on the preset frequency, the core unit model is analyzed using the finite element algorithm to obtain the system matrix equation of the core unit model; the system matrix equation is used to characterize the relationship between the system matrix, the degree of freedom vector on the preset side periodic boundary condition, the remaining degree of freedom vector and the load vector on the preset side periodic boundary condition, and other load vectors; the remaining degree of freedom vector represents the system degree of freedom vector except the degree of freedom on the preset side periodic boundary condition.

[0052] In an exemplary embodiment, see Figure 5 , Figure 5 is a flow chart of determining a system matrix equation of a core unit model provided by an embodiment of the present application. Step S403 may include:

[0053] S4031: Determine preset side periodic boundary conditions of the core unit model.

[0054] See also Figure 6 , Figure 6 The figure shows a schematic diagram of the structure of a unit model provided by an embodiment of the present application. In order to facilitate the understanding of the technical solution of the present application, the following first describes the various sides of any unit model. Generally, the unit model after slicing is a rectangular block, including a relative front (parallel to the xz plane) and a rear, a relative left (parallel to the yz plane) and a right. In the subsequent cascading process, the left and right sides can also be referred to as cascading faces. Optionally, the core unit model after meshing is composed of multiple three-dimensional geometric mesh units, and the cross-section of the mesh unit can be a rectangle, a triangle or a trapezoid, etc., which is not limited here.

[0055] Optionally, for different slicing methods, the periodic boundary conditions that need to be applied later are also different, that is, the preset side periodic boundary conditions are different. For the longitudinal slicing model, the preset side periodic boundary conditions include the front periodic boundary conditions corresponding to the front and the back periodic boundary conditions corresponding to the back; for the transverse slicing model, the left periodic boundary conditions and the right periodic boundary conditions corresponding to the left and right sides, respectively, need to be applied.

[0056] S4033: Based on the preset frequency, the core unit model is meshed and characteristic parameters are extracted using the finite element algorithm to obtain the system matrix and the system degree of freedom vector matrix; the system degree of freedom vector matrix includes the degree of freedom vectors on the preset side periodic boundary conditions and the remaining degree of freedom vectors.

[0057] In the frequency domain finite element method, after the unit model is meshed as described above, there are four physical field solutions to be solved at each grid point: (u, v, w, φ) T , where u, v, w are the X, Y, and Z components of the particle displacement respectively; φ is the electric potential at the grid point. The variables to be solved on all grid points are called degrees of freedom, and are arranged in a certain order as a degree of freedom vector X to construct the physical connection between adjacent grid points. Through finite element operations, the finite element system equation can be obtained:

[0058] A·X=F

[0059] Among them, A is the system matrix, with a size of N×N (N is the total number of degrees of freedom). This matrix is ​​only related to the differential equations (control equations) of the multi-physics field and the geometry of the solution domain, and has nothing to do with the boundary condition settings. F is the load vector, which is generated by meshing the unit structure, and when the linear constraint is not applied, the load vector is a zero vector. In particular, the system matrix of the frequency domain finite element can be composed of the stiffness matrix k and the mass matrix M:

[0060] A=K-ω 2 M

[0061] Among them, ω represents a parameter, and stiffness is a measure of the deformation ability of an object, that is, the size of the object's ability to resist deformation. The stiffness matrix K is a generalization of stiffness from one dimension to multiple dimensions, and takes into account the correlation between dimensions in the case of multiple dimensions. The mass matrix M is a generalization of mass from one dimension to multiple dimensions. It partially describes the kinetic energy of the system, depends on the position vector and changes with time. By solving the finite element system equations, all degrees of freedom of the system (SAW device model) can be obtained.

[0062] In this embodiment, the system matrix A in step S4031 is a 3x3 block matrix, which is expressed as the following matrix:

[0063]

[0064] S4035: Determine the system matrix equation of the core unit model based on the system matrix, the system degree of freedom vector matrix, the load vector on the preset side periodic boundary conditions and other load vectors.

[0065] In an exemplary embodiment, the core unit model includes a first side surface and a second side surface that are arranged opposite to each other; the preset side surface periodic boundary conditions include periodic boundary conditions on the first side surface and periodic boundary conditions on the second side surface; Figure 7 , Figure 7 FIG. 4 is a flow chart of another method for determining a system matrix equation of a core unit model provided by an embodiment of the present application. Step S4035 may include:

[0066] S701: Determine the number of degree of freedom vectors of periodic boundary conditions on the first side, the number of degree of freedom vectors of periodic boundary conditions on the second side, and the number of remaining degree of freedom vectors.

[0067] In this embodiment, see Figure 6 , the slice model is a longitudinal slice model, the first side may refer to the front, and the second side may refer to the back.

[0068] S703: Sort the remaining degree of freedom vectors, the degree of freedom vectors of the periodic boundary conditions on the first side surface, and the degree of freedom vectors of the periodic boundary conditions on the second side surface in sequence to form a system degree of freedom vector matrix.

[0069] In this embodiment, the system degree of freedom vector matrix X is the following matrix:

[0070]

[0071] Among them, F represents the degree of freedom vector on the periodic boundary condition on the first side, the number is n'; the degree of freedom vector on the periodic boundary condition on the second side, the number is n'; I represents the remaining degree of freedom vectors, the number is N-2n'.

[0072] S705: Sort the remaining load vectors, the load vector of the periodic boundary condition on the first side, and the load vector of the periodic boundary condition on the second side in sequence to form a system load matrix; the load vector of the periodic boundary condition on the first side and the load vector of the periodic boundary condition on the second side are inverse numbers of each other.

[0073] In this embodiment, the system load matrix is ​​expressed as follows:

[0074]

[0075] Wherein, L represents the remaining load vector; +f represents the load vector of the periodic boundary condition on the first side; and -f represents the load vector of the periodic boundary condition on the second side.

[0076] S707: Based on the number of degree of freedom vectors of periodic boundary conditions on the first side, the number of degree of freedom vectors of periodic boundary conditions on the second side, and the number of remaining degree of freedom vectors, the initial system matrix is ​​processed in blocks to obtain the system matrix.

[0077] In this embodiment, the system matrix in step S707 is the system matrix A in the above step S4031.

[0078] S709: Determine the system matrix equation of the core unit model based on the system matrix, the system degree of freedom vector matrix and the system load matrix.

[0079] In this embodiment, the system matrix equation can be expressed as follows:

[0080]

[0081] The above step S709 can also be embodied in the form of equation group components, and the system equation group is:

[0082]

[0083] S405: Classify and rearrange the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model; the initial target matrix equation is used to characterize the relationship between the processed system matrix, the displacement vector on the preset surface, the degree of freedom vector on the cascade surface, the electric potential of the interdigital electrode and the load vector on the preset surface, the load vector on the cascade surface, and the charge of the interdigital electrode.

[0084] In an exemplary embodiment, the interdigitated electrodes include first interdigitated electrodes and second interdigitated electrodes arranged in a staggered manner; step S405 may include:

[0085] 1) Classifying and rearranging the system degree of freedom vector matrix and the system load matrix to obtain a first updated system degree of freedom vector matrix and a first updated system load matrix; the first updated system degree of freedom vector matrix includes the remaining degree of freedom vectors and the degree of freedom vectors of periodic boundary conditions; the first updated system load matrix includes the remaining load vectors and zero.

[0086] In this embodiment, the first update system degree of freedom vector matrix can be expressed as:

[0087]

[0088] Where, by using the continuous periodic boundary condition: Thus, P is defined.

[0089] First update the system load matrix, which can be expressed as:

[0090]

[0091] 2) Based on the first updated system degree of freedom vector matrix, each block matrix in the system matrix is ​​processed to obtain a first updated system matrix.

[0092] Step 2) can be specifically expressed as: 11 As the block matrix A' 11 ; Block matrix A 12 and the block matrix A 13 The sum is determined as the block matrix A' 12 ; Block matrix A 21 and the block matrix A 31 The sum is determined as the block matrix A' 11 ; Block matrix A 22 , block matrix A 23 , block matrix A 32 and the block matrix A 33 The sum is determined as the block matrix A' 11 ; Based on the block matrix A' 11 , the block matrix A' 12 , the block matrix A' 11 and the block matrix A' 11 , generate the first update system matrix; the first update system matrix is ​​expressed as:

[0093]

[0094] That is to say, the system matrix can be processed as follows:

[0095]

[0096] And using the continuous periodic boundary condition:

[0097] Therefore, the equation group in the above step S709 can be updated to the following equation group:

[0098]

[0099] Based on the above first updated system degree of freedom vector matrix, first updated system load matrix and first updated system matrix, the following first rearranged system matrix equation can be obtained:

[0100]

[0101] 3) Based on the type of the interdigital electrodes, the first updated system matrix, the first updated system degree of freedom vector matrix and the first updated system load matrix are classified and rearranged to obtain the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix; the rearranged system degree of freedom vector matrix includes the remaining degree of freedom vector, the potential of the first interdigital electrode and the potential of the second interdigital electrode; the rearranged system load matrix includes the remaining load vector, the charge of the first interdigital electrode and the charge of the second interdigital electrode; the remaining degree of freedom vector is the system degree of freedom vector except the potential of the first interdigital electrode and the potential of the second interdigital electrode; the remaining load vector is the system load vector except the load vector of the first interdigital electrode and the load vector of the second interdigital electrode.

[0102] Optionally, step 3) may include:

[0103] 3-1) Based on the type of the interdigital electrodes, the first update system degree of freedom vector matrix, the first update system load matrix and the first update system matrix are reclassified and divided to obtain a second update system degree of freedom vector matrix, a second update system load matrix and a second update system matrix; the second update system degree of freedom vector matrix includes the remaining degree of freedom vector, the potential vector of the first interdigital electrode and the potential vector of the second interdigital electrode; the second update system load matrix includes the remaining load vector, the load vector of the first interdigital electrode and the load vector of the second interdigital electrode; the second update system matrix is ​​expressed as:

[0104]

[0105] Wherein, I represents the residual degree of freedom; α represents the first interdigital electrode; and β represents the second interdigital electrode.

[0106] Specifically, the specific classification method in the above step 3-1) can be to reclassify the degree of freedom vector (I, P) according to different interdigital electrodes and floating potential settings, that is: in is the degree of freedom vector formed by the arrangement of the potential degrees of freedom belonging to the first interdigital electrode in the grid block, and the number is n α ; is the degree of freedom vector formed by the arrangement of the potential degrees of freedom belonging to the second interdigital electrode in the grid block, and the number is n β ; I0 is the degree of freedom vector (residual degree of freedom vector) formed by the arrangement of the remaining degrees of freedom, and its size is n0 = N-n'-n α -n β; α is used to indicate the first interdigital electrode; β is used to indicate the second interdigital electrode. Then the second rearranged system matrix equation after rearranging the first rearranged system matrix equation is expressed as:

[0107]

[0108] Among them, the second update system degree of freedom vector matrix can be expressed as:

[0109]

[0110] The second update system load matrix can be expressed as:

[0111]

[0112] In particular, the above second rearrangement system matrix equation can also be implemented in component form, and the specific equation group can be expressed as follows:

[0113]

[0114] 3-2) performing contraction and merging processing on the vectors in the second updated system degree of freedom vector matrix and the second updated system load matrix to obtain the rearranged system degree of freedom vector matrix and the rearranged system load matrix.

[0115] Because of which represents the potential vector on the first interdigital electrode. In fact, the potential vectors on the same interdigital electrode are equal, so V α To represent the potential of each grid point on the first interdigital electrode; by adding the load vectors of all grid points on the first interdigital electrode, Q α Similarly, by adding the load vectors of all grid points on the second interdigital electrode, we can get Q β ; Thus, the vectors in the second updated system degree of freedom vector matrix and the second updated system load matrix are contracted and merged to obtain the rearranged system degree of freedom vector matrix and the rearranged system load matrix.

[0116] Among them, the rearranged system degree of freedom vector matrix can be expressed as:

[0117]

[0118] The rearranged system load matrix can be expressed as:

[0119]

[0120] 3-3) Based on the rearranged system degree of freedom vector matrix, each block matrix in the second updated system matrix is ​​processed to obtain the rearranged system matrix.

[0121] Optionally, step 3-3) can be expressed as: based on the block matrix A Iα The transpose of the first row vector determines the block matrix a Iα ; and based on the block matrix A Iβ The transpose of the second row vector determines the block matrix a Iβ ; The dimension of the first row vector is the number of degrees of freedom on the first interdigital electrode, and all components are 1; The dimension of the second row vector is the number of degrees of freedom on the second interdigital electrode, and all components are 1; Based on the first row vector and the block matrix A αI Determine the block matrix a αI ; and based on the second row vector and the block matrix A βI Determine the block matrix a βI ; Based on the first row vector, block matrix A αα The transpose of the first row vector determines the block matrix a αα ; and based on the first row vector, block matrix A αβ The transpose of the second row vector determines the block matrix a αβ ; Based on the second row vector, block matrix A βα The transpose of the first row vector determines the block matrix a βα ; and based on the second row vector, the block matrix A ββ The transpose of the second row vector determines the block matrix a ββ ; Based on the block matrix a Iα , block matrix a Iβ , block matrix a αI , block matrix a βI , block matrix a αα , block matrix a ββ , block matrix a βα and the block matrix a ββ , generating the rearranged system matrix;

[0122] The rearranged system matrix is ​​expressed as:

[0123]

[0124] That is to say, in particular, when the model does not set other nonlinear boundary conditions except periodic boundary conditions, interdigital electrode voltage, and suspension point position, L0 should be a zero vector. The block matrices in the above matrix equation can be defined as:

[0125]

[0126] in, represents the first row vector, n α represents the number of degrees of freedom on the first interdigital electrode; represents the second row vector; n β represents the number of degrees of freedom on the second interdigital electrode.

[0127] The above rearranged system matrix equation can also be realized in component form. The specific equation group can be expressed as follows:

[0128]

[0129] The corresponding rearranged system matrix equation is expressed as follows:

[0130]

[0131] 4) Based on the preset surface and the cascade surface, the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix are classified, rearranged and internal degree of freedom eliminated in turn to obtain the initial target matrix equation of the core unit model.

[0132] Optionally, step 4) may include:

[0133] 4-1) Reclassify the remaining degree of freedom vectors in the rearranged system degree of freedom vector matrix according to the required displacement degree of freedom on the preset surface, degree of freedom on the cascade surface and the remaining internal degree of freedom to obtain the displacement vector on the preset surface, the degree of freedom vector on the left cascade surface, the degree of freedom vector on the right cascade surface and the remaining internal degree of freedom vectors.

[0134] That is to say, the degree of freedom vector I0 is reclassified and divided according to the required displacement degree of freedom on the preset surface, the degree of freedom on the cascade surface and the remaining internal degrees of freedom, that is, it is divided into (I inner ,I s ,I surface ), where I s is the displacement degree of freedom vector on the preset surface, the number is n s ;I surface is the degree of freedom vector on the cascade surface, which can be further divided into I surface =(I l ,I r ), whose numbers are n l ,n r ;I inner is the remaining internal degree of freedom vector, whose magnitude is n inner =N-n'-(n α -1)-(n β -1).

[0135] In this embodiment, see Figure 6The preset surface may refer to a surface parallel to the xz plane in the core unit model, which may be the front surface, the back surface, or a surface parallel to the xz plane between the front surface and the back surface.

[0136] 4-2) Based on the displacement vector on the preset surface, the degree of freedom vector on the left cascade surface, the degree of freedom vector on the right cascade surface, the remaining internal degree of freedom vectors, the potential vector of the first interdigitated electrode and the potential vector of the second interdigitated electrode, a quasi-target system degree of freedom vector matrix is ​​constructed.

[0137] 4-3) Based on the quasi-target system degree of freedom vector matrix, the rearranged system matrix is ​​processed in blocks to obtain the quasi-target system matrix.

[0138] 4-4) Based on the quasi-target system degree of freedom vector matrix, the rearranged system load matrix is ​​classified and processed to obtain a quasi-target system load matrix; the quasi-target system load includes the load vector on the preset surface, the load vector on the left cascade surface, the load vector on the right cascade surface, the remaining internal load vectors, the load amount of the first interdigitated electrode and the load amount of the second interdigitated electrode.

[0139] That is to say, the quasi-target system degree of freedom vector includes the remaining internal degree of freedom vectors, and the quasi-target system load matrix includes the remaining internal load vectors; and then the Schur complement algorithm is used to eliminate the internal degrees of freedom to obtain the initial target system matrix equation of the core unit model.

[0140] 4-5) Using the Schur complement algorithm, the remaining internal degree of freedom vectors in the quasi-target system degree of freedom vector matrix, the quasi-target system matrix and the quasi-target system load matrix are eliminated to obtain the initial target system matrix equation of the core unit model.

[0141] Use the Schur complement operation to replace the I in the quasi-target system matrix equation of the core unit model constructed in the above steps 4-2) to 4-4) inner The degree of freedom vector is eliminated to obtain the initial target system matrix equation of the core unit model:

[0142]

[0143] In particular, the above initial target system matrix equation can also be written in the following component form:

[0144]

[0145]

[0146] See also Figure 4The above is an explanation of steps S401-405, and the following will continue to explain the subsequent step S407.

[0147] S407: Based on the initial target matrix equation of the core unit model, cascade processing is performed on each unit model to obtain a target matrix equation of the surface acoustic wave device model.

[0148] In an exemplary embodiment, step S407 may include:

[0149] 5) Preprocessing the initial target matrix equation of the core unit model to obtain the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model.

[0150] See also Figure 8 , Figure 8 The schematic diagram of the process of cascading two adjacent unit models. The two adjacent unit models are cascaded preprocessed, and the system matrix of the left unit model (unit model A) is recorded as B L , the initial target matrix equation of the left unit model can be expressed as follows:

[0151]

[0152] The system matrix of the unit model on the right (unit model B) is denoted as B R , the initial target matrix equation of the unit model on the right is expressed as follows:

[0153]

[0154] 6) The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure.

[0155] Optionally, the displacement vector on the preset surface in the initial target system degree of freedom vector matrix of the left unit model is recorded as The degree of freedom vector on the left cascade surface includes The displacement vector in the initial target system degree of freedom vector matrix of the right unit model is recorded as The degree of freedom vector on the right cascade surface includes Degrees of freedom in the new element model obtained after cascading Through analysis, the following relationship exists:

[0156]

[0157] Based on the above relationship, the initial target matrix equation of the left unit model is preprocessed, that is, expanded, reordered and divided into blocks to obtain the target matrix equation of the left unit model:

[0158]

[0159] The system matrix corresponding to the target matrix equation of the unit model on the left, that is, the third updated system matrix is ​​recorded as B' L The matrix (7 by 7 block matrix) is represented as:

[0160]

[0161] Wherein, L represents the left unit model; s represents the preset surface;

[0162] Similarly, by preprocessing the initial target matrix equation of the right unit model, that is, expanding, reordering and dividing it into blocks, the target matrix equation of the right unit model is obtained:

[0163]

[0164] The system matrix corresponding to the target matrix equation of the unit model on the right, that is, the fourth updated system matrix is ​​recorded as B' R The matrix (7 by 7 block matrix) is represented as:

[0165]

[0166] Among them, R represents the right unit model;

[0167] 7) Based on the number of unit models corresponding to the core unit model, the target matrix equation of the left unit model and the target matrix equation of the right unit model are cascaded to obtain the target matrix equation of the surface acoustic wave device model.

[0168] Optionally, when the number of the core unit models is greater than or equal to three, and the number of unit models corresponding to each of the core unit models is greater than or equal to three, step 7) may include:

[0169] 7-1) For each core unit model, two unit models to be processed are determined from the set of unit models to be processed of the core unit model; and the two unit models to be processed are respectively determined as the left unit model and the right unit model.

[0170] Continuing with the previous example, if Figure 2The longitudinal slice model shown in the figure may include that the corresponding interdigitated electrode region includes only one core unit model, and any two unit models in the to-be-processed unit model set of the core unit model may be used as to-be-processed unit modules and distinguished between left and right.

[0171] 7-2) The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure.

[0172] Optionally, step 7-2) can be expressed as: based on the displacement vectors on the preset surface and the degree of freedom vectors on the left cascade surface in the initial target system degree of freedom vector matrix of the left unit model, and the displacement vectors on the preset surface and the degree of freedom vectors on the right cascade surface in the initial target system degree of freedom vector matrix of the right unit model, the initial target system degree of freedom vector matrix of the left unit model and the initial target system degree of freedom vector matrix of the right unit model are classified and rearranged to obtain the target system degree of freedom vector matrix of the left unit model and the target system degree of freedom vector matrix of the right unit model; based on the target system degree of freedom vector matrix of the left unit model, the initial target system matrix and the initial target system matrix of the left unit model are classified and rearranged. The initial target system load matrix is ​​expanded and rearranged to obtain the target system matrix and target system load matrix of the left unit model; based on the target system degree of freedom vector matrix of the right unit model, the initial target system matrix and the initial target system load matrix of the right unit model are expanded and rearranged to obtain the target system matrix and the target system load matrix of the right unit model; based on the target system degree of freedom vector matrix, the target system matrix and the target system load matrix of the left unit model, the target matrix equation of the left unit model is generated; based on the target system degree of freedom vector matrix, the target system matrix and the target system load matrix of the right unit model, the target matrix equation of the right unit model is generated.

[0173] As in step 6), the target system degree of freedom vector matrix of the left unit model and the target system degree of freedom vector matrix of the right unit model are respectively expressed as:

[0174]

[0175] The target system load matrix of the unit model on the left and the target system load matrix of the unit model on the right are expressed as:

[0176]

[0177] The target system matrix of the left unit model is the third updated system matrix mentioned above, denoted as B' L matrix; the target system matrix of the unit model on the right is the fourth updated system matrix mentioned above, denoted as B' R matrix.

[0178] By rearranging the different degree of freedom vectors in the left unit model and the right unit model into the same degree of freedom vector matrix, based on this, the system matrix and load matrix corresponding to the left and right unit models are rearranged, so that the left and right unit models can perform subsequent operations.

[0179] 7-3) Cascading the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain the initial cascade matrix equation of the target unit model; and using the Schur complement algorithm to eliminate the remaining internal degree of freedom vectors in the initial cascade matrix equation of the target unit model to obtain the quasi-target cascade matrix equation of the target unit model.

[0180] Among them, the fifth update system matrix (6 times 6 block matrix) in the initial cascade matrix equation of the target unit model can be expressed as:

[0181]

[0182] Furthermore, the fifth update system matrix can be abbreviated as A N , which is expressed as follows:

[0183]

[0184] The initial cascade matrix equation of the target unit model can be expressed as:

[0185]

[0186] Use the Schur complement operation to convert the above cascaded quasi-target matrix equation into Eliminate, get eliminated

[0187] The quasi-target cascade matrix equation of the target unit model is:

[0188]

[0189] In particular, the component form of the matrix is ​​completely consistent with the form of the initial target system matrix equation of the core unit model in step 3) of the above step S405 after completion.

[0190] 7-4) replacing two to-be-processed unit models in the to-be-processed unit model set with the target unit model; and using the target unit model as the to-be-processed unit model.

[0191] For multiple unit models corresponding to the core unit model, such as Figure 2 The longitudinal slice model shown can be divided into n unit models, assuming n=4, and the unit model set to be processed includes four unit models of the same structure, A, B, C and D. When the initial target matrix equation of the core unit model is known, the cascade can be performed according to the above steps 6), 7-1) to 7-3), and the quasi-target cascade matrix equation after the cascade of unit models AB can be obtained first. Then the unit model formed by the cascade of unit models A and B is the target unit model E, and the unit model set to be processed includes three unit models E, C and D to be processed.

[0192] 7-5) Repeatedly determine two unit models to be processed from the set of unit models to be processed of the core unit model; respectively determine the two unit models to be processed as the left unit model and the right unit model; respectively expand and rearrange the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure; the target matrix equation of the left unit model and the target matrix equation of the right unit model are respectively expanded and rearranged to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model. The target matrix equations of the unit models are cascaded to obtain the initial cascade matrix equations of the target unit models; and the remaining internal degree of freedom vectors in the initial cascade matrix equations of the target unit models are eliminated using the Schur complement algorithm to obtain the quasi-target cascade matrix equations of the target unit models; two unit models to be processed in the unit model set to be processed are replaced by the target unit model; and the target unit model is used as the unit model to be processed until the unit model set to be processed contains only one unit model to be processed, and the quasi-target cascade matrix equations of the unit models to be processed in the unit model set to be processed containing only one unit model to be processed are determined as the target cascade matrix equations of the core unit model.

[0193] Optionally, repeat the above steps 7-1) to 7-4) until the to-be-processed unit model set contains only one to-be-processed unit model, that is, the to-be-processed unit models A, B, C and D in the initial to-be-processed unit model set are all cascaded to obtain the target cascade matrix equation of the core unit model. The first cascade method can be used later, where E can be cascaded with C to obtain ABC, and then cascaded with D to obtain ABCD, cascading 3 times in total;

[0194] In order to improve the data processing efficiency, the second cascade method can also be used to obtain the quasi-target matrix equation after AB cascade. Since A, B, C and D are unit models with the same structure, the quasi-target matrix equation after AB cascade can be used as the quasi-target matrix equation after C and D cascade. The above two equations are then cascaded to obtain the quasi-target equation of the longitudinal slice model, that is, for the number of unit models is 2 2 , two cascades are required, that is, in the cascade process, the number of unit models can be converted into binary expression to determine the number of unit model cascades. For example, for the IDT region, there are 157 pairs of interdigital electrodes, that is, 157 unit models with the same structure, and the corresponding binary expression is 2 7 +2 4 +2 3 +2 2 +2 0 , it means that the number of cascades is 11 times. During the cascade process, the system matrices after 0, 2, 3 and 4 cascades can be stored as needed to facilitate calculations in subsequent cascade processes. If there is an additional unpaired electrode in the IDT region, the number of cascades is 12 times.

[0195] It should be noted that in the cascading process, especially the second cascading method, the post-cascading system matrix can be stored as needed for the required number of times, so that in the subsequent cascading process, the post-cascading system matrix of this type can be directly obtained to perform cascade calculations.

[0196] 7-6) Based on the number of the core unit models, the target cascade matrix equations of the core unit models are cascaded to obtain the target matrix equation of the surface acoustic wave device model.

[0197] Optionally, step 7-6) can be expressed as:

[0198] 7-6-1) Construct a set of core unit models to be processed based on each core unit model.

[0199] The set of core unit models to be processed includes a plurality of core unit models to be processed, and each core unit model to be processed may refer to a core unit model processed in cascade by the above steps 7-1) to 7-5).

[0200] For example, see Figure 2 The longitudinal slice model includes an IDT region and a reflective grating region, wherein the IDT region corresponds to the first core unit model and the reflective grating region corresponds to the second core unit model. The core unit model set to be processed includes 1 first core unit model and 2 second core unit models.

[0201] 7-6-2) According to the arrangement order of the core unit models in the core unit model set to be processed, two adjacent core unit models to be processed are determined from the core unit model set to be processed, and the two adjacent core unit models to be processed are respectively determined as the left unit model and the right unit model.

[0202] Continuing with the above example, the arrangement order of the core unit models in the core unit model set to be processed is the second core unit model, the first core unit model, and the second core unit model.

[0203] 7-6-3) The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model.

[0204] 7-6-4) Cascading the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain the initial cascade matrix equation of the target core unit model; and using the Schur complement algorithm to eliminate the remaining internal degrees of freedom in the initial cascade matrix equation of the target core unit model to obtain the quasi-target cascade matrix equation of the target core unit model.

[0205] 7-6-5) replacing the two adjacent core unit models to be processed in the core unit model set to be processed with the target core unit model; and using the target core unit model as the core unit model to be processed.

[0206] 7-6-6) Repeat the above steps according to the arrangement order of the core unit models in the core unit model set to be processed, determine two adjacent core unit models to be processed from the core unit model set to be processed, and determine the two adjacent core unit models to be processed as the left unit model and the right unit model respectively; expand and rearrange the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; cascade the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain the target core unit The invention discloses an initial cascade matrix equation of the model; and using the Schur complement algorithm to eliminate the remaining internal degrees of freedom in the initial cascade matrix equation of the target core unit model to obtain a quasi-target cascade matrix equation of the target core unit model; replacing the two adjacent core unit models to be processed with the target core unit model; and taking the target core unit model as the core unit model to be processed, until the core unit set to be processed contains only one core unit module to be processed, and determining the quasi-target cascade matrix equation of the core unit model to be processed in the core unit set to be processed containing only one core unit module to be processed as the target matrix equation of the surface acoustic wave device model.

[0207] In this embodiment, the cascading process of all the core unit models to be processed in the core unit model set to be processed is similar to the above-mentioned process of cascading the unit model set to be processed. Compared with the unit model set to be processed, when the core unit model set to be processed is cascaded, it usually includes core unit models of different structures, and therefore the above-mentioned first cascading method is mainly adopted.

[0208] Through the above steps, the SAW device model can be cascaded, such as Fig. 9 As shown, PML is a perfectly matched layer.

[0209] The target matrix equation of the device can be obtained as follows:

[0210]

[0211] The above is only an example. In fact, whether it is the core unit structure or the repeated unit structure corresponding to the core unit structure, there are a large number of them after actual segmentation. In the cascading process, it is necessary to first determine the type of unit structure, that is, which type of corresponding core unit structure is, as well as the number and type of adjacent unit structures, so that a suitable cascading method can be selected. The same type of cascading can adopt the second cascading method, and different types of unit structure cascading can adopt the first method.

[0212] S409: Determine the displacement vector on the preset surface and the charge amount of the interdigital electrodes based on the target matrix equation of the surface acoustic wave device model.

[0213] First, the B matrix in the target matrix equation is known. Usually, the voltage of the interdigital electrodes in the SAW device model is set: α Set to 1V, V β Set to 0V, based on the above target matrix equation, the total charge accumulated on the first interdigital electrode can be derived: Define E11 as Then we can get the following formula:

[0214]

[0215] Secondly, solve the degree of freedom of the preset surface in the target matrix equation in step S407 First, invert the B matrix in the above target matrix equation to obtain [C] = [B] -1 , we can get the following processed target matrix equation:

[0216]

[0217] Furthermore, we can deduce and solve Specifically, The calculation formula is as follows:

[0218]

[0219] S411: Determine the wave number domain vibration mode distribution result and admittance of the surface acoustic wave device model based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes.

[0220] In an exemplary embodiment, step S411 may include: performing two-dimensional Fourier transform processing on the displacement vector on the preset surface to obtain the wave number domain vibration mode distribution result of the surface acoustic wave device model; determining the admittance of the surface acoustic wave device model based on the potential matrix of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes.

[0221] Generally, the admittance Y 11 The calculation formula of (ω) is as follows:

[0222]

[0223] Wherein, i is an imaginary unit, and ω represents a preset frequency.

[0224] See also Fig.10 and 11, respectively a spatial domain vibration mode diagram and a wave number domain vibration mode diagram provided in the embodiment of the present application. The spatial domain vibration mode diagram is used to represent the distribution of the degrees of freedom on the preset surface of the longitudinal slice model provided in the present application. Fig.10 The data is transformed into two-dimensional Fourier transform, that is, the vibration mode distribution result in the wave number domain, and the Fig.11 The wavenumber domain vibration diagram is shown.

[0225] As can be seen from the above technical solutions of the embodiments of the present application, this solution provides the fastest simulation algorithm that can simultaneously solve the admittance and other displacement degrees of freedom that the user wishes to solve, without complicated and cumbersome post-processing steps. Solved the problem that the simulation of HCT-FEM cannot simultaneously solve other displacement degrees of freedom other than admittance. The HCT-FEM simulation method requires additional post-processing-that is, the inverse process of its cascade algorithm to solve the corresponding displacement degrees of freedom, which will cause the simulation time to increase greatly, thereby offsetting the advantage of the extremely fast simulation that the HCT-FEM algorithm has compared to the traditional FEM algorithm. This solution does not require a cascade inverse process, and all matrix operations can be further accelerated by a professional computing acceleration card (such as NVIDIA Tesla A10080G), so that this solution still has the advantage of extremely short simulation time. This solution realizes the joint simulation of finite element-two-dimensional fast Fourier transform, and its finite element part has flexible output and solution options, which can provide strong support for more joint simulations and subsequent data analysis.

[0226] Corresponding to the simulation methods of the surface acoustic wave device provided in the above-mentioned embodiments, the embodiment of the present application also provides a simulation device of the surface acoustic wave device. Since the simulation device of the surface acoustic wave device provided in the embodiment of the present application corresponds to the simulation methods of the surface acoustic wave device provided in the above-mentioned embodiments, the implementation methods of the simulation methods of the aforementioned surface acoustic wave devices are also applicable to the simulation device of the surface acoustic wave device provided in this embodiment, and will not be described in detail in this embodiment.

[0227] See also Fig.12 , which is a schematic diagram of the structure of a simulation device for a surface acoustic wave device provided in an embodiment of the present application, the device has the function of implementing the simulation method for the surface acoustic wave device in the above method embodiment, and the function can be implemented by hardware, or by hardware executing corresponding software. Fig.12 As shown, the device may include:

[0228] A segmentation module 1201 is used to segment and identify the surface acoustic wave device model to obtain a core unit model corresponding to the multiple unit models;

[0229] The analytical module 1203 is used to analyze the core unit model based on the preset frequency using the finite element algorithm to obtain the system matrix equation of the core unit model; the system matrix equation is used to characterize the relationship between the system matrix, the degree of freedom vector on the preset side periodic boundary condition, the remaining degree of freedom vector and the load vector on the preset side periodic boundary condition, and other load vectors; the remaining degree of freedom vector represents the system degree of freedom vector except the degree of freedom on the preset side periodic boundary condition;

[0230] The classification and rearrangement module 1205 is used to classify and rearrange the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model; the initial target matrix equation is used to characterize the relationship between the processed system matrix, the displacement vector on the preset surface, the degree of freedom vector on the cascade surface, the potential of the interdigital electrode and the load vector on the preset surface, the load vector on the cascade surface, and the charge of the interdigital electrode;

[0231] A cascade processing module 1207 is used to perform cascade processing on each unit model based on the initial target matrix equation of the core unit model to obtain a target matrix equation of the surface acoustic wave device model;

[0232] A first determination module 1209 is used to determine the displacement vector on the preset surface and the charge amount of the interdigital electrodes based on the target matrix equation of the surface acoustic wave device model;

[0233] The second determination module 1211 is used to determine the wave number domain vibration mode distribution result and admittance of the surface acoustic wave device model based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes.

[0234] In an exemplary embodiment, the analytical module is used to determine the preset lateral periodic boundary conditions of the core unit model;

[0235] Based on the preset frequency, the core unit model is meshed and the characteristic parameters are extracted using the finite element algorithm to obtain the system matrix and the system degree of freedom vector matrix; the system degree of freedom vector matrix includes the degree of freedom vectors on the preset side periodic boundary conditions and the remaining degree of freedom vectors;

[0236] The system matrix equation of the core unit model is determined based on the system matrix, the system degree of freedom vector matrix, the load vector on the preset side periodic boundary conditions and other load vectors.

[0237] In an exemplary embodiment, the core unit model includes a first side surface and a second side surface that are relatively arranged; the preset side periodic boundary conditions include periodic boundary conditions on the first side surface and periodic boundary conditions on the second side surface; the system matrix equation of the core unit model is determined based on the system matrix, the system degree of freedom vector matrix, the load vector on the preset side periodic boundary conditions and other load vectors, including:

[0238] Determining the number of degree of freedom vectors for the periodic boundary conditions on the first side, the number of degree of freedom vectors for the periodic boundary conditions on the second side, and the number of remaining degree of freedom vectors;

[0239] The remaining degree of freedom vectors, the degree of freedom vectors of the periodic boundary conditions on the first side surface, and the degree of freedom vectors of the periodic boundary conditions on the second side surface are sequentially sorted to form a system degree of freedom vector matrix;

[0240] The remaining load vectors, the load vector of the periodic boundary condition on the first side surface, and the load vector of the periodic boundary condition on the second side surface are sequentially sorted to form a system load matrix; the load vector of the periodic boundary condition on the first side surface and the load vector of the periodic boundary condition on the second side surface are inverse numbers of each other;

[0241] The initial system matrix is ​​processed in blocks based on the number of degree of freedom vectors of the periodic boundary conditions on the first side, the number of degree of freedom vectors of the periodic boundary conditions on the second side, and the number of remaining degree of freedom vectors to obtain a system matrix;

[0242] The system matrix equation of the core unit model is determined based on the system matrix, the system degree of freedom vector matrix and the system load matrix.

[0243] In an exemplary embodiment, the interdigitated electrodes include first interdigitated electrodes and second interdigitated electrodes arranged in a staggered manner; the system matrix is ​​a 3×3 block matrix, which is expressed as:

[0244]

[0245] A classification and rearrangement module is used to classify and rearrange the system degree of freedom vector matrix and the system load matrix to obtain a first updated system degree of freedom vector matrix and a first updated system load matrix; the first updated system degree of freedom vector matrix includes the remaining degree of freedom vectors and the degree of freedom vectors of the periodic boundary conditions; the first updated system load matrix includes the remaining load vectors and zero;

[0246] Based on the first updated system degree of freedom vector matrix, each block matrix in the system matrix is ​​processed to obtain a first updated system matrix;

[0247] Based on the type of interdigital electrodes, the first updated system matrix, the first updated system degree of freedom vector matrix and the first updated system load matrix are classified and rearranged to obtain a rearranged system matrix, a rearranged system degree of freedom vector matrix and a rearranged system load matrix; the rearranged system degree of freedom vector matrix includes a residual degree of freedom vector, the potential of the first interdigital electrode, the potential of the second interdigital electrode; the rearranged system load matrix includes a residual load vector, the charge of the first interdigital electrode and the charge of the second interdigital electrode; the residual degree of freedom vector is the system degree of freedom vector divided by the potential of the first interdigital electrode and the potential of the second interdigital electrode; the residual load vector is the system load vector divided by the load vector of the first interdigital electrode and the load vector of the second interdigital electrode;

[0248] Based on the preset surfaces and cascade surfaces, the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix are classified, rearranged and the internal degrees of freedom are eliminated in turn to obtain the initial target matrix equation of the core unit model.

[0249] In an exemplary embodiment, the classification rearrangement module is used to transform the block matrix A 11 As the block matrix A' 11 ;

[0250] The block matrix A 12 and the block matrix A 13 The sum is determined as the block matrix A' 12 ;

[0251] The block matrix A 21 and the block matrix A 31 The sum is determined as the block matrix A' 11 ;

[0252] The block matrix A 22 , block matrix A 23 , block matrix A 32 and the block matrix A 33 The sum is determined as the block matrix A' 11 ;

[0253] Based on the block matrix A' 11 , block matrix A' 12 , block matrix A' 11 and the block matrix A' 11 , generate the first updated system matrix; the first updated system matrix is ​​expressed as:

[0254]

[0255] In an exemplary embodiment, the classification rearrangement module is used to reclassify and divide the first update system degree of freedom vector matrix, the first update system load matrix and the first update system matrix based on the type of the interdigital electrodes, respectively, to obtain the second update system degree of freedom vector matrix, the second update system load matrix and the second update system matrix; the second update system degree of freedom vector matrix includes the remaining degree of freedom vector, the potential vector of the first interdigital electrode and the potential vector of the second interdigital electrode; the second update system load matrix includes the remaining load vector, the load vector of the first interdigital electrode and the load vector of the second interdigital electrode; the second update system matrix is ​​expressed as:

[0256]

[0257] Wherein, I represents the residual degree of freedom; α represents the first interdigital electrode; β represents the second interdigital electrode;

[0258] Perform contraction and merging processing on the vectors in the second updated system degree of freedom vector matrix and the second updated system load matrix to obtain a rearranged system degree of freedom vector matrix and a rearranged system load matrix;

[0259] Based on the rearranged system degree of freedom vector matrix, each block matrix in the second updated system matrix is ​​processed to obtain the rearranged system matrix.

[0260] In an exemplary embodiment, the classification rearrangement module is used to classify the block matrix A based on Iα The transpose of the first row vector determines the block matrix a Iα ; and based on the block matrix A Iβ The transpose of the second row vector determines the block matrix a Iβ ; The dimension of the first row vector is the number of degrees of freedom on the first interdigital electrode, and all components are 1; the dimension of the second row vector is the number of degrees of freedom on the second interdigital electrode, and all components are 1;

[0261] Based on the first row vector and the block matrix A αI Determine the block matrix a αI ; and based on the second row vector and the block matrix A βI Determine the block matrix a βI ;

[0262] Based on the first row vector, block matrix A αα The transpose of the first row vector determines the block matrix a αα ; and based on the first row vector, block matrix A αβ The transpose of the second row vector determines the block matrix a αβ ;

[0263] Based on the second row vector, block matrix A βαThe transpose of the first row vector determines the block matrix a βα ; and based on the second row vector, the block matrix A ββ The transpose of the second row vector determines the block matrix a ββ ;

[0264] Based on the block matrix a Iα , block matrix a Iβ , block matrix a αI , block matrix a βI , block matrix a αα , block matrix a ββ , block matrix a βα and the block matrix a ββ , generate the rearranged system matrix;

[0265] The rearranged system matrix is ​​expressed as:

[0266]

[0267] In an exemplary embodiment, a classification and rearrangement module is used to reclassify the remaining degree of freedom vectors in the rearranged system degree of freedom vector matrix according to the required displacement degree of freedom on the preset surface, the degree of freedom on the cascade surface, and the remaining internal degrees of freedom, to obtain the displacement vector on the preset surface, the degree of freedom vector on the left cascade surface, the degree of freedom vector on the right cascade surface, and the remaining internal degree of freedom vectors;

[0268] Based on the displacement vector on the preset surface, the degree of freedom vector on the left cascade surface, the degree of freedom vector on the right cascade surface, the remaining internal degree of freedom vectors, the potential vector of the first interdigital electrode and the potential vector of the second interdigital electrode, a degree of freedom vector matrix of the quasi-target system is constructed;

[0269] Based on the degree of freedom vector matrix of the quasi-target system, the rearranged system matrix is ​​processed in blocks to obtain the quasi-target system matrix;

[0270] Based on the quasi-target system degree of freedom vector matrix, the rearranged system load matrix is ​​classified and processed to obtain the quasi-target system load matrix; the quasi-target system load includes the load vector on the preset surface, the load vector on the left cascade surface, the load vector on the right cascade surface, the remaining internal load vectors, the load amount of the first interdigital electrode and the load amount of the second interdigital electrode;

[0271] The Schur complement algorithm is used to eliminate the remaining internal degree of freedom vectors in the quasi-target system degree of freedom vector matrix, the quasi-target system matrix and the quasi-target system load matrix, and the initial target system matrix equation of the core unit model is obtained.

[0272] In an exemplary embodiment, the cascade processing module is used to preprocess the initial target matrix equation of the core unit model to obtain the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model;

[0273] The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure;

[0274] Based on the number of unit models corresponding to the core unit model, the target matrix equation of the unit model on the left and the target matrix equation of the unit model on the right are cascaded to obtain the target matrix equation of the surface acoustic wave device model.

[0275] In an exemplary embodiment, when the number of core unit models is greater than or equal to three, and the number of unit models corresponding to each core unit model is greater than or equal to three, the cascade processing module is used to determine, for each core unit model, two unit models to be processed from the set of unit models to be processed of the core unit model; and determine the two unit models to be processed as a left unit model and a right unit model respectively;

[0276] The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure;

[0277] The target matrix equation of the left unit model and the target matrix equation of the right unit model are cascaded to obtain the initial cascade matrix equation of the target unit model; and the remaining internal degree of freedom vectors in the initial cascade matrix equation of the target unit model are eliminated by using the Schur complement algorithm to obtain the quasi-target cascade matrix equation of the target unit model;

[0278] Replacing two to-be-processed unit models in the to-be-processed unit model set with the target unit model; and using the target unit model as the to-be-processed unit model;

[0279] Repeatedly determine two unit models to be processed from the set of unit models to be processed of the core unit model; determine the two unit models to be processed as the left unit model and the right unit model respectively; expand and rearrange the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure; the target matrix equation of the left unit model and the target matrix equation of the right unit model are respectively expanded and rearranged to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model. Cascading the target matrix equations to obtain the initial cascade matrix equations of the target unit model; and using the Schur complement algorithm to eliminate the remaining internal degree of freedom vectors in the initial cascade matrix equations of the target unit model to obtain the quasi-target cascade matrix equations of the target unit model; replacing the two unit models to be processed in the unit model set to be processed with the target unit model; and taking the target unit model as the unit model to be processed until the unit model set to be processed contains only one unit model to be processed, and determining the quasi-target cascade matrix equations of the unit models to be processed in the unit model set to be processed containing only one unit model to be processed as the target cascade matrix equations of the core unit model;

[0280] Based on the number of core unit models, the target cascade matrix equations of the core unit models are cascaded to obtain the target matrix equation of the surface acoustic wave device model.

[0281] In an exemplary embodiment, the third updated system matrix in the target matrix equation of the left unit model is expressed as:

[0282]

[0283] Wherein, L represents the left unit model; s represents the preset surface;

[0284] The fourth updated system matrix in the objective matrix equation of the right-hand unit model is expressed as:

[0285]

[0286] Among them, R represents the right unit model;

[0287] The fifth update system matrix in the initial cascade matrix equation is expressed as:

[0288]

[0289] In an exemplary embodiment, the cascade processing module is used to construct a set of core unit models to be processed based on each core unit model;

[0290] According to the arrangement order of the core unit models in the processing core unit model set, two adjacent core unit models to be processed are determined from the core unit model set to be processed, and the two adjacent core unit models to be processed are respectively determined as a left unit model and a right unit model;

[0291] The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model;

[0292] The target matrix equation of the left unit model and the target matrix equation of the right unit model are cascaded to obtain the initial cascade matrix equation of the target core unit model; and the remaining internal degrees of freedom in the initial cascade matrix equation of the target core unit model are eliminated by using the Schur complement algorithm to obtain the quasi-target cascade matrix equation of the target core unit model;

[0293] Replacing two adjacent core unit models to be processed in the core unit model set to be processed with the target core unit model; and using the target core unit model as the core unit model to be processed;

[0294] Repeat the above steps according to the arrangement order of the core unit models in the core unit model set, determine two adjacent core unit models to be processed from the core unit set to be processed, and determine the two adjacent core unit models to be processed as the left unit model and the right unit model respectively; expand and rearrange the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; cascade the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain the initial target core unit model. The invention discloses a method for preparing a quasi-target cascade matrix equation of a target core unit model; and using the Schur complement algorithm to eliminate the remaining internal degrees of freedom in the initial cascade matrix equation of the target core unit model to obtain a quasi-target cascade matrix equation of the target core unit model; and replacing two adjacent core unit models to be processed with the target core unit model; and taking the target core unit model as the core unit model to be processed, until the core unit set to be processed contains only one core unit module to be processed, and determining the quasi-target cascade matrix equation of the core unit model to be processed in the core unit set to be processed containing only one core unit module to be processed as the target matrix equation of the surface acoustic wave device model.

[0295] In an exemplary embodiment, the cascade processing module is used to classify and rearrange the initial target system degree of freedom vector matrix of the left unit model and the initial target system degree of freedom vector matrix of the right unit model based on the displacement vector on the preset surface and the degree of freedom vector on the left cascade surface in the initial target system degree of freedom vector matrix of the left unit model, and the displacement vector on the preset surface and the degree of freedom vector on the right cascade surface in the initial target system degree of freedom vector matrix of the right unit model, to obtain the target system degree of freedom vector matrix of the left unit model and the target system degree of freedom vector matrix of the right unit model;

[0296] Based on the target system degree of freedom vector matrix of the left unit model, the initial target system matrix and the initial target system load matrix of the left unit model are expanded and rearranged to obtain the target system matrix and the target system load matrix of the left unit model;

[0297] Based on the target system degree of freedom vector matrix of the right unit model, the initial target system matrix and the initial target system load matrix of the right unit model are expanded and rearranged to obtain the target system matrix and the target system load matrix of the right unit model;

[0298] Based on the target system degree of freedom vector matrix, target system matrix and target system load matrix of the left unit model, generate the target matrix equation of the left unit model;

[0299] Based on the target system degree of freedom vector matrix, the target system matrix and the target system load matrix of the right-side unit model, a target matrix equation of the right-side unit model is generated.

[0300] In an exemplary embodiment, the second determination module is used to perform a two-dimensional Fourier transform process on the displacement vector on the preset surface to obtain a wave number domain vibration mode distribution result of the surface acoustic wave device model;

[0301] The admittance of the surface acoustic wave device model is determined based on the potential matrix of the interdigital electrodes, a preset frequency, and a preset voltage of the interdigital electrodes.

[0302] It should be noted that the device provided in the above embodiment, when implementing its functions, is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0303] An embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement any one of the surface acoustic wave device simulation methods provided in the above method embodiments.

[0304] The memory can be used to store software programs and modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs required for functions, etc.; the data storage area can store data created according to the use of the device, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory can also include a memory controller to provide the processor with access to the memory.

[0305] The method embodiments provided in the embodiments of the present application may be executed in a computer terminal, a server or a similar computing device, that is, the above-mentioned electronic device may include a computer terminal, a server or a similar computing device. Fig.13 This is a hardware structure block diagram of an electronic device for running a method for simulating a surface acoustic wave device provided in an embodiment of the present application. The simulation device for the surface acoustic wave device may participate in or include the simulation apparatus for the surface acoustic wave device provided in an embodiment of the present application. Fig.13 As shown, the simulation device 130 of the surface acoustic wave device may include one or more (1302a, 1302b, ..., 1302n are used to illustrate in the figure) processors 1302 (the processor 1302 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 1304 for storing data, and a transmission device 1306 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Fig.13 The structure shown is only for illustration and does not limit the structure of the electronic device. Fig.13 More or fewer components as shown, or with Fig.13 Different configurations are shown.

[0306] It should be noted that the one or more processors 1302 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the surface acoustic wave device simulation device 130 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0307] The memory 1304 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the simulation method of the surface acoustic wave device described in the embodiment of the present application. The processor 1302 executes various functional applications and data processing by running the software programs and modules stored in the memory 1304, that is, realizing the above-mentioned simulation method of a surface acoustic wave device. The memory 1304 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 1304 may further include a memory remotely arranged relative to the processor 1302, and these remote memories may be connected to the simulation device 130 of the surface acoustic wave device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0308] The transmission device 1306 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the surface acoustic wave device simulation device 130. In one example, the transmission device 1306 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one embodiment, the transmission device 1306 can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet wirelessly.

[0309] The display may be, for example, a touch screen type liquid crystal display (LCD), which may enable a user to interact with a user interface of the surface acoustic wave device simulation device 130 (or a mobile device).

[0310] An embodiment of the present application also provides a computer-readable storage medium, which can be set in an electronic device to store at least one instruction or at least one program related to implementing a simulation method for a surface acoustic wave device. The at least one instruction or the at least one program is loaded and executed by the processor to implement any one of the simulation methods for surface acoustic wave devices provided in the above method embodiments.

[0311] The embodiment of the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. The processor of the electronic device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the electronic device executes any one of the surface acoustic wave device simulation methods provided in the above method embodiments.

[0312] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store program codes.

[0313] It should be noted that the above-mentioned sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above-mentioned specific embodiments of this specification are described. Other embodiments are within the scope of the attached claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0314] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0315] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0316] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for simulating a surface acoustic wave device, characterized in that: The method comprises: Segmenting and identifying the surface acoustic wave device model to obtain a core unit model corresponding to the multiple unit models; Based on the preset frequency, the core unit model is analyzed and processed using a finite element algorithm to obtain a system matrix equation of the core unit model; the system matrix equation is used to characterize the relationship between the system matrix, the system degree of freedom vector matrix and the system load matrix; the system degree of freedom vector matrix includes the degree of freedom vector on the preset side periodic boundary condition and the remaining degree of freedom vectors; the remaining degree of freedom vector represents the system degree of freedom vector except the degree of freedom on the preset side periodic boundary condition; the core unit model includes a first side and a second side that are relatively set; the preset side periodic boundary condition includes a periodic boundary condition on the first side and a periodic boundary condition on the second side; the system load matrix is ​​constructed by sorting in sequence according to other load vectors, the load vector of the periodic boundary condition on the first side and the load vector of the periodic boundary condition on the second side; the load vector of the periodic boundary condition on the first side and the load vector of the periodic boundary condition on the second side are mutually inverse numbers; Classifying and rearranging various parameters in the system matrix equation of the core unit model to obtain an initial target matrix equation of the core unit model; the initial target matrix equation is used to characterize the relationship between the rearranged system matrix, the displacement vector on the preset surface, the degree of freedom vector on the cascade surface, the electric potential of the interdigital electrode and the load vector on the preset surface, the load vector on the cascade surface, and the charge amount of the interdigital electrode; the interdigital electrode includes a first interdigital electrode and a second interdigital electrode arranged in a staggered manner; Based on the initial target matrix equation of the core unit model, cascade processing is performed on each unit model to obtain the target matrix equation of the surface acoustic wave device model; Determining the displacement vector on the preset surface and the charge amount of the interdigital electrodes based on the target matrix equation of the surface acoustic wave device model; Determine the wave number domain mode distribution result and admittance of the surface acoustic wave device model based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes; The classifying and rearranging of the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model includes: Classifying and rearranging the system degree of freedom vector matrix and the system load matrix to obtain a first updated system degree of freedom vector matrix and a first updated system load matrix; the first updated system degree of freedom vector matrix includes the remaining degree of freedom vectors and the degree of freedom vectors of the periodic boundary conditions; the first updated system load matrix includes the other load vectors and zero; Based on the first updated system degree of freedom vector matrix, each block matrix in the system matrix is ​​processed to obtain a first updated system matrix; Based on the type of the interdigital electrodes, the first updated system matrix, the first updated system degree of freedom vector matrix and the first updated system load matrix are classified and rearranged to obtain the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix; the rearranged system degree of freedom vector matrix includes a residual degree of freedom vector, the potential of the first interdigital electrode and the potential of the second interdigital electrode; the rearranged system load matrix includes a residual load vector, the charge of the first interdigital electrode and the charge of the second interdigital electrode; the residual degree of freedom vector is the system degree of freedom vector divided by the potential of the first interdigital electrode and the potential of the second interdigital electrode; the residual load vector is the system load vector divided by the load vector of the first interdigital electrode and the load vector of the second interdigital electrode; Based on the preset surface and the cascade surface, the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix are sequentially classified, rearranged and internal degree of freedom eliminated to obtain the initial target matrix equation of the core unit model.

2. The simulation method according to claim 1, characterized in that: Based on the preset frequency, the core unit model is analyzed using a finite element algorithm to obtain a system matrix equation of the core unit model; The system matrix equation is used to characterize the relationship between the system matrix, the system degree of freedom vector matrix and the system load matrix, including: Determining preset side periodic boundary conditions of the core unit model; Based on the preset frequency, the core unit model is meshed and characteristic parameters are extracted using a finite element algorithm to obtain the system matrix and the system degree of freedom vector matrix; The system matrix equation of the core unit model is determined based on the system matrix, the system degree of freedom vector matrix, the load vector on the preset side periodic boundary condition and the other load vectors.

3. The simulation method according to claim 2, characterized in that: The system matrix equation of the core unit model is determined based on the system matrix, the system degree of freedom vector matrix, the load vector on the preset side periodic boundary condition and the other load vectors, including: Determine the number of degree of freedom vectors of the periodic boundary conditions on the first side, the number of degree of freedom vectors of the periodic boundary conditions on the second side, and the number of remaining degree of freedom vectors; Sorting the remaining degree of freedom vectors, the degree of freedom vector of the periodic boundary condition on the first side surface, and the degree of freedom vector of the periodic boundary condition on the second side surface in sequence to form the system degree of freedom vector matrix; Sorting the other load vectors, the load vector of the periodic boundary condition on the first side surface, and the load vector of the periodic boundary condition on the second side surface in sequence to form a system load matrix; Based on the number of degree of freedom vectors of the periodic boundary conditions on the first side, the number of degree of freedom vectors of the periodic boundary conditions on the second side, and the number of the remaining degree of freedom vectors, the initial system matrix is ​​processed in blocks to obtain the system matrix; A system matrix equation of the core unit model is determined based on the system matrix, the system degree of freedom vector matrix and the system load matrix.

4. The simulation method according to claim 3, characterized in that: The system matrix is ​​a 3 by 3 block matrix, expressed as:

5. The simulation method according to claim 4, characterized in that: The method of processing each block matrix in the system matrix based on the first updated system degree of freedom vector matrix to obtain a first updated system matrix includes: The block matrix A 11 As the block matrix A′ 11 ; The block matrix A 12 and the block matrix A 13 The sum is determined as the block matrix A′ 12 ; The block matrix A 21 and the block matrix A 31 The sum is determined as the block matrix A′ 11 ; The block matrix A 22 , block matrix A 23 , block matrix A 32 and the block matrix A 33 The sum is determined as the block matrix A′ 11 ; Based on the block matrix A′ 11 , the block matrix A′ 12 , the block matrix A′ 11 and the block matrix A′ 11 , generate the first update system matrix; the first update system matrix is ​​expressed as:

6. The simulation method according to claim 5, characterized in that: The first updated system matrix, the first updated system degree of freedom vector matrix and the first updated system load matrix are classified and rearranged based on the type of the interdigital electrodes to obtain the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix, including: Based on the type of the interdigital electrodes, the first update system degree of freedom vector matrix, the first update system load matrix and the first update system matrix are reclassified and divided to obtain a second update system degree of freedom vector matrix, a second update system load matrix and a second update system matrix; the second update system degree of freedom vector matrix includes the remaining degree of freedom vector, the potential vector of the first interdigital electrode and the potential vector of the second interdigital electrode; the second update system load matrix includes the remaining load vector, the load vector of the first interdigital electrode and the load vector of the second interdigital electrode; the second update system matrix is ​​expressed as: Wherein, I represents the residual degree of freedom; α represents the first interdigital electrode; β represents the second interdigital electrode; Performing contraction and merging processing on the vectors in the second updated system degree of freedom vector matrix and the second updated system load matrix to obtain the rearranged system degree of freedom vector matrix and the rearranged system load matrix; Based on the rearranged system degree of freedom vector matrix, each block matrix in the second updated system matrix is ​​processed to obtain the rearranged system matrix.

7. The simulation method according to claim 6, characterized in that: The step of processing each block matrix in the second updated system matrix based on the rearranged system degree of freedom vector matrix to obtain the rearranged system matrix includes: Based on the block matrix A Iα The transpose of the first row vector determines the block matrix a Iα ; and based on the block matrix A Iβ The transpose of the second row vector determines the block matrix a Iβ ; The dimension of the first row vector is the number of degrees of freedom on the first interdigital electrode, and all components are 1; the dimension of the second row vector is the number of degrees of freedom on the second interdigital electrode, and all components are 1; Based on the first row vector and the block matrix A αI Determine the block matrix a αI ; and based on the second row vector and the block matrix A βI Determine the block matrix a βI ; Based on the first row vector, the block matrix A αα The transpose of the first row vector determines the block matrix a αα ; and based on the first row vector, the block matrix A αβ and the transpose of the second row vector determines the block matrix a αβ ; Based on the second row vector, the block matrix A βα The transpose of the first row vector determines the block matrix a βα ; and based on the second row vector, the block matrix A ββ and the transpose of the second row vector determines the block matrix a ββ ; Based on the block matrix a Iα , the block matrix a Iβ , the block matrix a αI , the block matrix a βI , the block matrix a αα , the block matrix a ββ , the block matrix a βα and the block matrix a ββ , generating the rearranged system matrix; The rearranged system matrix is ​​expressed as:

8. The simulation method according to claim 7, characterized in that: Based on the preset surface and the cascade surface, the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix are sequentially classified, rearranged and internal degree of freedom eliminated to obtain the initial target matrix equation of the core unit model, including: Reclassify the remaining degree of freedom vectors in the rearranged system degree of freedom vector matrix according to the required displacement degree of freedom on the preset surface, the degree of freedom on the cascade surface, and the remaining internal degrees of freedom to obtain the displacement vector on the preset surface, the degree of freedom vector on the left cascade surface, the degree of freedom vector on the right cascade surface, and the remaining internal degree of freedom vectors; Constructing a quasi-target system degree of freedom vector matrix based on the displacement vector on the preset surface, the degree of freedom vector on the left cascade surface, the degree of freedom vector on the right cascade surface, the remaining internal degree of freedom vectors, the potential vector of the first interdigital electrode, and the potential vector of the second interdigital electrode; Based on the quasi-target system degree of freedom vector matrix, the rearranged system matrix is ​​processed in blocks to obtain a quasi-target system matrix; Based on the quasi-target system degree of freedom vector matrix, the rearranged system load matrix is ​​classified and processed to obtain a quasi-target system load matrix; the quasi-target system load includes a load vector on the preset surface, a load vector on the left cascade surface, a load vector on the right cascade surface, other internal load vectors, a load amount of the first interdigital electrode, and a load amount of the second interdigital electrode; The Schur complement algorithm is used to eliminate the remaining internal degree of freedom vectors in the quasi-target system degree of freedom vector matrix, the quasi-target system matrix and the quasi-target system load matrix to obtain the initial target system matrix equation of the core unit model.

9. The simulation method according to claim 8, characterized in that: The initial target matrix equation based on the core unit model, cascading each unit model to obtain the target matrix equation of the surface acoustic wave device model, includes: Preprocessing the initial target matrix equation of the core unit model to obtain the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model; The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure; Based on the number of unit models corresponding to the core unit model, the target matrix equation of the left unit model and the target matrix equation of the right unit model are cascaded to obtain the target matrix equation of the surface acoustic wave device model.

10. The simulation method according to claim 9, characterized in that: When the number of the core unit models is greater than or equal to three, and the number of unit models corresponding to each of the core unit models is greater than or equal to three, the target matrix equation of the left unit model and the target matrix equation of the right unit model are cascaded based on the number of unit models corresponding to the core unit model to obtain the target matrix equation of the surface acoustic wave device model, including: For each core unit model, two unit models to be processed are determined from the set of unit models to be processed of the core unit model; the two unit models to be processed are respectively determined as the left unit model and the right unit model; The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure; Cascading the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain an initial cascade matrix equation of the target unit model; and eliminating the remaining internal degree of freedom vectors in the initial cascade matrix equation of the target unit model using a Schur complement algorithm to obtain a quasi-target cascade matrix equation of the target unit model; Replacing two to-be-processed unit models in the to-be-processed unit model set with the target unit model; and using the target unit model as the to-be-processed unit model; Repeatedly determine two unit models to be processed from the set of unit models to be processed of the core unit model; respectively determine the two unit models to be processed as the left unit model and the right unit model; respectively expand and rearrange the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; the target system degree of freedom vector matrix in the target matrix equation of the left unit model and the target system degree of freedom vector matrix in the target matrix equation of the right unit model are system degree of freedom vector matrices with the same structure; the target matrix equation of the left unit model and the target matrix equation of the right unit model are respectively expanded and rearranged to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model. The target matrix equation of the model is cascaded to obtain the initial cascade matrix equation of the target unit model; and the remaining internal degree of freedom vectors in the initial cascade matrix equation of the target unit model are eliminated by using the Schur complement algorithm to obtain the quasi-target cascade matrix equation of the target unit model; the two unit models to be processed in the unit model set to be processed are replaced by the target unit model; and the target unit model is used as the unit model to be processed until the unit model set to be processed contains only one unit model to be processed, and the quasi-target cascade matrix equation of the unit model to be processed in the unit model set to be processed containing only one unit model to be processed is determined as the target cascade matrix equation of the core unit model; Based on the number of the core unit models, the target cascade matrix equations of the core unit models are cascaded to obtain the target matrix equation of the surface acoustic wave device model.

11. The simulation method according to claim 10, characterized in that: The third updated system matrix in the objective matrix equation of the left unit model is expressed as: Wherein, L represents the left unit model; s represents the preset surface; The fourth updated system matrix in the objective matrix equation of the right-hand unit model is expressed as: Among them, R represents the right unit model; The fifth update system matrix in the initial cascade matrix equation is expressed as:

12. The simulation method according to claim 11, characterized in that: The target cascade matrix equations of the core unit models are cascaded based on the number of the core unit models to obtain the target matrix equation of the surface acoustic wave device model, including: Construct a set of core unit models to be processed based on each core unit model; According to the arrangement order of the core unit models in the core unit model set to be processed, two adjacent core unit models to be processed are determined from the core unit model set to be processed, and the two adjacent core unit models to be processed are respectively determined as the left unit model and the right unit model; The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; Cascading the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain an initial cascade matrix equation of the target core unit model; and using the Schur complement algorithm to eliminate the remaining internal degrees of freedom in the initial cascade matrix equation of the target core unit model to obtain a quasi-target cascade matrix equation of the target core unit model; Replacing the two adjacent core unit models to be processed in the core unit model set to be processed with the target core unit model; and using the target core unit model as the core unit model to be processed; Repeat the above steps according to the arrangement order of the core unit models in the core unit model set to be processed, determine two adjacent core unit models to be processed from the core unit model set to be processed, and determine the two adjacent core unit models to be processed as the left unit model and the right unit model respectively; expand and rearrange the initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model; cascade the target matrix equation of the left unit model and the target matrix equation of the right unit model to obtain the target core unit model. An initial cascade matrix equation; and using the Schur complement algorithm to eliminate the remaining internal degrees of freedom in the initial cascade matrix equation of the target core unit model to obtain a quasi-target cascade matrix equation of the target core unit model; replacing the two adjacent core unit models to be processed with the target core unit model; and using the target core unit model as the core unit model to be processed, until the core unit set to be processed contains only one core unit module to be processed, and determining the quasi-target cascade matrix equation of the core unit model to be processed in the core unit set to be processed that contains only one core unit module to be processed as the target matrix equation of the surface acoustic wave device model.

13. The simulation method according to claim 10, characterized in that: The initial target matrix equation of the left unit model and the initial target matrix equation of the right unit model are expanded and rearranged respectively to obtain the target matrix equation of the left unit model and the target matrix equation of the right unit model, including: Based on the displacement vectors on the preset surface and the degree of freedom vectors on the left cascade surface in the initial target system degree of freedom vector matrix of the left unit model, and the displacement vectors on the preset surface and the degree of freedom vectors on the right cascade surface in the initial target system degree of freedom vector matrix of the right unit model, the initial target system degree of freedom vector matrix of the left unit model and the initial target system degree of freedom vector matrix of the right unit model are classified and rearranged to obtain the target system degree of freedom vector matrix of the left unit model and the target system degree of freedom vector matrix of the right unit model; Based on the target system degree of freedom vector matrix of the left unit model, the initial target system matrix and the initial target system load matrix of the left unit model are expanded and rearranged to obtain the target system matrix and the target system load matrix of the left unit model; Based on the target system degree of freedom vector matrix of the right unit model, the initial target system matrix and the initial target system load matrix of the right unit model are expanded and rearranged to obtain the target system matrix and the target system load matrix of the right unit model; Generate a target matrix equation of the left unit model based on a target system degree of freedom vector matrix, a target system matrix and a target system load matrix of the left unit model; Based on the target system degree of freedom vector matrix, the target system matrix and the target system load matrix of the right-side unit model, a target matrix equation of the right-side unit model is generated.

14. The simulation method according to claim 1, characterized in that: The step of determining the wave number domain mode shape diagram and admittance of the surface acoustic wave device model based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes comprises: Performing a two-dimensional Fourier transform process on the displacement vector on the preset surface to obtain a wave number domain vibration mode distribution result of the surface acoustic wave device model; The admittance of the surface acoustic wave device model is determined based on the potential matrix of the interdigital electrodes, the preset frequency, and the preset voltage of the interdigital electrodes.

15. A simulation device for a surface acoustic wave device, characterized in that: The device comprises: A segmentation module is used to segment and identify the surface acoustic wave device model to obtain a core unit model corresponding to multiple unit models; An analytical module is used to analyze the core unit model based on a preset frequency using a finite element algorithm to obtain a system matrix equation of the core unit model; the system matrix equation is used to characterize the relationship between the system matrix, the system degree of freedom vector matrix and the system load matrix; the system degree of freedom vector matrix includes the degree of freedom vector on the preset side periodic boundary condition and the remaining degree of freedom vectors; the remaining degree of freedom vector represents the system degree of freedom vector except the degree of freedom on the preset side periodic boundary condition; the core unit model includes a first side and a second side that are relatively set; the preset side periodic boundary condition includes the periodic boundary condition on the first side and the periodic boundary condition on the second side; the system load matrix is ​​constructed by sorting in sequence according to other load vectors, the load vector of the periodic boundary condition on the first side and the load vector of the periodic boundary condition on the second side; the load vector of the periodic boundary condition on the first side and the load vector of the periodic boundary condition on the second side are inverse numbers of each other; A classification and rearrangement module is used to classify and rearrange the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model; the initial target matrix equation is used to characterize the relationship between the rearranged system matrix, the displacement vector on the preset surface, the degree of freedom vector on the cascade surface, the electric potential of the interdigital electrode and the load vector on the preset surface, the load vector on the cascade surface, and the charge of the interdigital electrode; the interdigital electrode includes a first interdigital electrode and a second interdigital electrode arranged in a staggered manner; A cascade processing module, used for performing cascade processing on each unit model based on the initial target matrix equation of the core unit model to obtain the target matrix equation of the surface acoustic wave device model; A first determination module, used for determining the displacement vector on the preset surface and the charge amount of the interdigital electrode based on the target matrix equation of the surface acoustic wave device model; A second determination module is used to determine the wave number domain vibration mode distribution result and admittance of the surface acoustic wave device model based on the displacement vector on the preset surface, the charge amount of the interdigital electrodes, the preset frequency and the preset voltage of the interdigital electrodes; The classifying and rearranging of the parameters in the system matrix equation of the core unit model to obtain the initial target matrix equation of the core unit model includes: Classifying and rearranging the system degree of freedom vector matrix and the system load matrix to obtain a first updated system degree of freedom vector matrix and a first updated system load matrix; the first updated system degree of freedom vector matrix includes the remaining degree of freedom vectors and the degree of freedom vectors of the periodic boundary conditions; the first updated system load matrix includes the other load vectors and zero; Based on the first updated system degree of freedom vector matrix, each block matrix in the system matrix is ​​processed to obtain a first updated system matrix; Based on the type of the interdigital electrodes, the first updated system matrix, the first updated system degree of freedom vector matrix and the first updated system load matrix are classified and rearranged to obtain the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix; the rearranged system degree of freedom vector matrix includes a residual degree of freedom vector, the potential of the first interdigital electrode and the potential of the second interdigital electrode; the rearranged system load matrix includes a residual load vector, the charge of the first interdigital electrode and the charge of the second interdigital electrode; the residual degree of freedom vector is the system degree of freedom vector divided by the potential of the first interdigital electrode and the potential of the second interdigital electrode; the residual load vector is the system load vector divided by the load vector of the first interdigital electrode and the load vector of the second interdigital electrode; Based on the preset surface and the cascade surface, the rearranged system matrix, the rearranged system degree of freedom vector matrix and the rearranged system load matrix are sequentially classified, rearranged and internal degree of freedom eliminated to obtain the initial target matrix equation of the core unit model.

16. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the simulation method of the surface acoustic wave device according to any one of claims 1 to 14.

17. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by a processor to implement the simulation method of a surface acoustic wave device according to any one of claims 1 to 14.

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