Temperature characteristic iterative simulation method and system for elastic wave device, and related device

Abstract

The present invention is applicable to the technical field of piezoelectric simulation, particularly relates to a temperature characteristic iterative simulation method and system for an elastic wave device, and a related device. The temperature characteristic iterative simulation method for an elastic wave device provided by the present invention takes into consideration the impact of self-heating of the elastic wave device on the device performance as well as the heat transfer condition of the environment where the device is located, and achieves full coupling of solid mechanics, static electricity and a heat transfer field by means of iterative optimization of solutions across simulation models, thus improving the prediction capability for the temperature drift performance of devices in a simulation design stage, and the accuracy of temperature drift simulation of acoustic devices.

Description

Temperature characteristic iterative simulation method and system of elastic wave device and related equipment TECHNICAL FIELD

[0001] The application belongs to the technical field of piezoelectric simulation, and particularly relates to a temperature characteristic iterative simulation method and system of an elastic wave device and related equipment. BACKGROUND

[0002] The working frequency of an elastic wave device based on a surface acoustic wave (SAW) or a bulk acoustic wave (BAW) will drift with temperature changes, and this characteristic is referred to as temperature drift. Temperature drift characteristics can cause the passband of a product such as a filter to shift, affecting the insertion loss of the passband, especially the insertion loss of the passband edge position and the out-of-band suppression. During the design stage of the elastic wave device, it is necessary to reduce temperature drift as much as possible, appropriately widen the range of the passband, reduce the transition band range, ensure that the shifted passband can still cover the target frequency band, and ensure that the out-of-band suppression can still meet the index requirements. Therefore, improving the temperature drift performance prediction capability of the design end will greatly reduce the resource consumption of device design and speed up product iteration.

[0003] Generally, since the vibration heat and electric heat of the elastic wave device are very small, the influence of the temperature field (ambient temperature) can be ignored, and therefore only the one-way action of the temperature field on the device is considered. The action of the temperature field mainly includes two aspects: 1. Thermal expansion and contraction of the solid, which will produce thermal stress and strain, and through the stress-strain relationship, a one-way action on the mechanical field is produced; 2. Thermal sensitivity of the material, the material properties will change with temperature, and the change of the material properties produces a one-way action on the mechanical field and the electric field. Different elastic wave device designs under high and low temperature environments, when high power is input, due to the self-heating effect and piezoelectric effect of the device, the temperature field, the mechanical field and the electric field will interact, and this kind of problem belongs to a strong coupling problem of multiple physical fields.

[0004] The temperature drift prediction model of the related technology only considers the influence of the change of the ambient temperature on the temperature drift of the elastic wave device, and these prediction models ignore the regional temperature change caused by the self-heating of the device when the input power is large, thereby causing a large disturbance to the performance of the device. In addition, the current prediction method does not consider the heat transfer conditions of the environment where the device is located, thereby leading to inaccurate prediction of the temperature. SUMMARY

[0005] The application provides a temperature characteristic iterative simulation method and system of an elastic wave device and related equipment, and aims to solve the problem of inaccurate temperature drift prediction caused by not considering the thermal effect in the temperature characteristic simulation of the elastic wave device in the prior art.

[0006] To solve the above technical problems, in a first aspect, the application provides a temperature characteristic iterative simulation method of an elastic wave device, comprising the following steps:

[0007] S101: establish a two-dimensional model of an elastic wave device;

[0008] S102: modify the two-dimensional model, increase a material parameter of the elastic wave device in a parameter of the two-dimensional model, and obtain a characteristic two-dimensional model;

[0009] S103: establish a three-dimensional equivalent heat transfer model of the elastic wave device;

[0010] S104: perform simulation based on the three-dimensional equivalent heat transfer model, and obtain an environmental thermal resistance R of the elastic wave device;

[0011] S105: perform simulation on the characteristic two-dimensional model based on the environmental thermal resistance R, and obtain a device loss Qh and an admittance Y of the elastic wave device at an ambient temperature T i-1 i i ;

[0012] S106: determine whether a preset condition is met between Qh i and Qh i-1 , if yes, execute step 108; if no, execute step S107;

[0013] S107: substitute the device loss Qh i into a preset iterative optimization algorithm to obtain an iterative value Qh_itera, calculate a current temperature T i of the elastic wave device according to the iterative value, simultaneously set i=i+1, and return to step S105;

[0014] S108: output the device loss Qh i-1 and the admittance Y i of the elastic wave device at the temperature T i as a temperature characteristic simulation result.

[0015] Further, the preset iterative optimization algorithm is a Newton iteration method, a gradient is defined as grad_Qh, a Newton step size is step_size_newton, a preset step size is step_size, a device loss is Qh i , an iterative value is Qh_itera, and the current temperature T i satisfies the following relationship: grad_Qh=(Qh_itera-Qh i ) / Qh i ; step_size_newton=min(abs(step_size), abs(Qh i ​​Qh_itera = Qh_itera - step_size_newton * grad_Qh; T i = R * Qh_itera;

[0016] Wherein, min is the minimum function, abs is the absolute value function.

[0017] Further, the preset condition is:

[0018] Qh i = Qh i-1 ; or,

[0019] Qh i and Qh i-1 satisfy a preset relative tolerance; or

[0020] Qh i and Qh i-1 satisfy a preset absolute tolerance.

[0021] Further, step S102 is specifically:

[0022] The thermal expansion coefficient of the two-dimensional model is modified, and a is defined i (T) represents the corresponding thermal expansion coefficient of the elastic wave device at working temperature T, a i (T0) represents the corresponding thermal expansion coefficient of the elastic wave device at ambient temperature T0, which satisfies the following relationship (1):

[0023] Wherein, Both represent constants;

[0024] The elastic constant, piezoelectric constant, dielectric constant and density of the two-dimensional model are modified, and C ijkl (T) represents the elastic constant at working temperature T, e kij (T) represents the piezoelectric constant at working temperature T, ε kj (T) represents the dielectric constant at working temperature T, and p(T) represents the density at working temperature T, which satisfies the following relationship (2):

[0025] Wherein, Both represent the material property coefficients of the elastic wave device.

[0026] Further, step S104 is specifically:

[0027] Mark the heat source in the three-dimensional equivalent heat transfer model, obtain the heat generation power Q' of the heat source, simulate the three-dimensional equivalent heat transfer model to obtain the average temperature T' of the heat source, and the environmental thermal resistance R satisfies: R=T' / Q'.

[0028] In a second aspect, the present application further provides a temperature characteristic iterative simulation system of an elastic wave device, comprising:

[0029] A two-dimensional modeling module is configured to establish a two-dimensional model of the elastic wave device.

[0030] A thermal conversion module is configured to modify the two-dimensional model, increase the material parameters of the elastic wave device in the parameters of the two-dimensional model, and obtain a characteristic two-dimensional model.

[0031] A three-dimensional modeling module is configured to establish a three-dimensional equivalent heat transfer model of the elastic wave device.

[0032] A three-dimensional simulation module is configured to simulate based on the three-dimensional equivalent heat transfer model to obtain the environmental thermal resistance R of the elastic wave device.

[0033] A two-dimensional simulation module is configured to simulate the characteristic two-dimensional model based on the environmental thermal resistance R to obtain the device loss Qh and the admittance Y of the elastic wave device at the ambient temperature T i-1 i i

[0034] A judgment module is configured to determine whether the preset condition is met between Qh i and Qh i-1 , if yes, execute the output module, and if no, execute the iteration module.

[0035] An iteration module is configured to substitute the device loss Qh i into a preset iterative optimization algorithm to obtain an iteration value Qh_itera, calculate the current temperature T i of the elastic wave device according to the iteration value, simultaneously set i=i+1, and return to the judgment module.

[0036] An output module is configured to output the device loss Qh i-1 and the admittance Y i of the elastic wave device at the temperature T i as the temperature characteristic simulation result.

[0037] Further, the preset iterative optimization algorithm is the Newton iteration method, the gradient is defined as grad_Qh, the Newton step size is step_size_newton, the preset step size is step_size, the device loss is Qh i , the iteration value is Qh_itera, and the current temperature T​​​i satisfies the following relationship: grad_Qh=(Qh_itera-Qh i ) / Qh i ; step_size_newton=min(abs(step_size),abs(Qh i / grad_Qh)); Qh_itera=Qh_itera-step_size_newton*grad_Qh; T i =R*Qh_itera;

[0038] Wherein, min is the minimum function, and abs is the absolute value function.

[0039] Further, the preset condition is:

[0040] Qh i ==Qh i-1 ; or,

[0041] Qh i and Qh i-1 satisfy a preset relative tolerance; or

[0042] Qh i and Qh i-1 satisfy a preset absolute tolerance.

[0043] In a third aspect, the present application also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the elastic wave device temperature characteristic iterative simulation method in any one of the above embodiments.

[0044] In a fourth aspect, the present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executable on a processor to implement the steps of the elastic wave device temperature characteristic iterative simulation method in any one of the above embodiments.

[0045] The present application has the advantages that the elastic wave device temperature characteristic iterative simulation method considers the influence of self-heating of the elastic wave device on the device performance and the heat transfer condition of the environment where the device is located, realizes full coupling of solid mechanics, electrostatics and heat transfer field through iterative optimization of solutions between simulation models, improves the prediction ability of the device temperature drift performance in the simulation design stage, and improves the accuracy of acoustic device temperature drift simulation. BRIEF DESCRIPTION OF DRAWINGS

[0046] Fig. 1 is a step flow chart of a temperature characteristic iterative simulation method of an elastic wave device according to an embodiment of the present application;

[0047] Fig. 2 is a modeling schematic diagram of a two-dimensional model according to an embodiment of the present application;

[0048] Fig. 3 is a modeling schematic diagram of a three-dimensional equivalent heat transfer model according to an embodiment of the present application;

[0049] Fig. 4 is a device loss simulation result schematic diagram according to an embodiment of the present application;

[0050] Fig. 5 is a temperature simulation result schematic diagram according to an embodiment of the present application;

[0051] Fig. 6 is an admittance simulation result schematic diagram according to an embodiment of the present application;

[0052] Fig. 7 is a structure schematic diagram of a temperature characteristic iterative simulation system of an elastic wave device according to an embodiment of the present application;

[0053] Fig. 8 is a structure schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0055] Please refer to Fig. 1, which is a step flow chart of a temperature characteristic iterative simulation method of an elastic wave device according to an embodiment of the present application. The temperature characteristic iterative simulation method comprises the following steps:

[0056] S101: establishing a two-dimensional model of an elastic wave device.

[0057] In the embodiment of the present application, the two-dimensional model is modeled based on a finite element simulation software. The finite element simulation software can be used to establish a SAW single device, a BAW device, other piezoelectric devices or a filter formed by cascading devices, and the structure of the specific device does not affect the method flow of the embodiment of the present application. For example, the modeling of a two-dimensional model of a single SAW device with a lithium niobate LiNbO3 substrate is shown in Fig. 2.

[0058] S102: modifying the two-dimensional model, adding material parameters of the elastic wave device to the parameters of the two-dimensional model, to obtain a characteristic two-dimensional model.

[0059] The main purpose of this step is to consider the thermal expansion and material thermal physical field of the two-dimensional model, so that the two-dimensional model is expressed by a constant relationship to a temperature-dependent relationship. Step S102 is specifically:

[0060] The thermal expansion coefficient of the two-dimensional model is modified, and the thermal expansion coefficient refers to the relative change amount of the length or volume of the object per unit length, per unit volume when the temperature rises by 1℃. The thermal expansion coefficient is generally expressed in the form of Taylor expansion. Specifically, the thermal expansion coefficient is defined as α i (T) represents the corresponding thermal expansion coefficient of the elastic wave device at the working temperature T, and α i (T0) represents the corresponding thermal expansion coefficient of the elastic wave device at the ambient temperature T0, and satisfies the following relationship (1):

[0061] wherein, Both represent constants.

[0062] The elastic constant, piezoelectric constant, dielectric constant and density of the two-dimensional model are modified, and C ijkl (T) represents the elastic constant at the working temperature T, e kij (T) represents the piezoelectric constant at the working temperature T, ε kj (T) represents the dielectric constant at the working temperature T, and ρ(T) represents the density at the working temperature T, which satisfies the following relationship (2):

[0063] wherein, Both represent the material property coefficients of the elastic wave device.

[0064] In the specific implementation process, in some cases, the metal film TCR and other parameters also need to be considered for the metal electrode.

[0065] S103: Establish a three-dimensional equivalent heat transfer model of the elastic wave device.

[0066] Similarly, the three-dimensional equivalent heat transfer model can also be modeled based on finite element simulation software. The three-dimensional equivalent heat transfer model corresponding to FIG. 2 is shown in FIG. 3.

[0067] S104: Based on the three-dimensional equivalent heat transfer model, simulation is performed to obtain the environmental thermal resistance R of the elastic wave device.

[0068] Step S104 specifically includes:

[0069] In the three-dimensional equivalent heat transfer model, mark the heat source, such as the dark area in FIG. 3, obtain the heat power Q' of the heat source, and perform simulation operation on the three-dimensional equivalent heat transfer model to obtain the average temperature T' of the heat source. The environmental thermal resistance R satisfies: R=T' / Q'.

[0070] Figure 3 shows a heat transfer model with a single heat source site. In the implementation process, for other devices such as filters based on device cascade, step S104 can calculate the thermal resistance by obtaining the environmental thermal resistance matrix.

[0071] As shown in Figure 1, steps S101-S102 and steps S103-S104 are respectively used for different types of modeling, and the steps have no certain sequence.

[0072] S105: Based on the environmental thermal resistance R, simulate the characteristic two-dimensional model to obtain the device loss Qh of the elastic wave device at the ambient temperature T0 i-1 i and admittance Y i .

[0073] The simulation of this step is mainly carried out by acoustic frequency domain simulation, at this time the simulation parameters need to be set, including but not limited to input signal frequency freq, ambient temperature T0, input power P, etc. Qh can be a built-in loss operator of finite element simulation software, such as Qh.tot, etc., or a loss data calculated by current and voltage. In the embodiment of the present application, the total power consumption operator Qh=solid.Qh_tot, P=1W, and T0 is room temperature.

[0074] S106: Determine whether Qh i and Qh i-1 meet the preset condition, if yes, execute step 108; if no, execute step S107. The preset condition is:

[0075] Qh i == Qh i-1 ; or,

[0076] Qh i and Qh i-1 meet the preset relative tolerance; or

[0077] Qh i and Qh i-1 meet the preset absolute tolerance.

[0078] S107: Substitute the device loss Qh i into the preset iterative optimization algorithm to obtain the iterative value Qh_itera, and calculate the current temperature T i of the elastic wave device according to the iterative value Qh_itera×R, at the same time make i=i+1, return to step S105.

[0079] ​The preset iterative optimization algorithm is a Newton iteration method, a gradient is defined as grad_Qh, a Newton step size is step_size_newton, a preset step size is step_size, a device loss is Qh i , an iteration value is Qh_itera, and the current temperature T i satisfies the following relationship: grad_Qh=(Qh_itera-Qh i ) / Qh i ; step_size_newton=min(abs(step_size), abs(Qh i / grad_Qh)); Qh_itera=Qh_itera-step_size_newton×grad_Qh; T i =R×Qh_itera.

[0080] Wherein, min is a minimum value function, and abs is an absolute value function.

[0081] According to the steps of the Newton iteration method, the gradient grad_Qh is first calculated, then the Newton step size step_size_newton is calculated, the absolute value of the step size is not more than the minimum value of step_size or Qh i / grad_Qh; finally, the optimization parameters Qh_itera and T i are updated using the Newton iteration formula. In step S107, the model parameters are set according to the current parameter value in each iteration, the parameters are updated by calculating the gradient, and whether the convergence condition is reached is judged, and finally the optimized parameter value is obtained.

[0082] S108: Output the device loss Qh i-1 and the admittance Y i of the elastic wave device at the temperature T i as the temperature characteristic simulation result.

[0083] The simulation results shown in FIGS. 4-6 are provided as examples by the embodiments of the present application, wherein FIG. 4 is a simulation result of the device loss Qh at different frequencies when the input power is 1W, FIG. 5 is a simulation result of the temperature T at different frequencies when the input power is 1W, and FIG. 6 is a simulation result of the admittance Y at different frequencies when the input power is 1W, A, B and C in each figure are respectively the frequency response curves of i as an initial value, i as an intermediate value, and i as an iteration convergence value. It can be seen that the temperature characteristic iteration simulation method proposed in the embodiments of the present application reflects the influence of temperature change on the device loss and the admittance in the simulation process, which is beneficial to predicting the required temperature drift data in the device design process.

[0084] The beneficial effect achieved by this invention lies in proposing an iterative simulation method for the temperature characteristics of elastic wave devices. This method considers the influence of the self-heating of elastic wave devices on device performance, as well as the heat transfer conditions of the environment in which the device is located. Through iterative optimization of solutions between simulation models, it realizes the full coupling of solid mechanics, electrostatics, and heat transfer fields, thereby improving the ability to predict the temperature drift performance of devices in the simulation design stage and the accuracy of temperature drift simulation of acoustic devices.

[0085] This invention also provides an iterative simulation system 200 for the temperature characteristics of an elastic wave device. Referring to Figure 7, which is a schematic diagram of the structure of the iterative simulation system for the temperature characteristics of an elastic wave device provided in this invention, it includes:

[0086] Two-dimensional modeling module 201 is used to establish a two-dimensional model of the elastic wave device;

[0087] The thermal-material conversion module 202 is used to modify the two-dimensional model by adding the material parameters of the elastic wave device to the parameters of the two-dimensional model to obtain a characteristic two-dimensional model.

[0088] The three-dimensional modeling module 203 is used to establish a three-dimensional equivalent heat transfer model of the elastic wave device;

[0089] The three-dimensional simulation module 204 is used to perform simulation based on the three-dimensional equivalent heat transfer model to obtain the environmental thermal resistance R of the elastic wave device.

[0090] The two-dimensional simulation module 205 is used to simulate the characteristic two-dimensional model based on the environmental thermal resistance R, and obtain the elastic wave device at an environmental temperature T. i-1 The device loss Qh i and admittance Y i ;

[0091] Module 206 is used to determine Qh i With Qh i-1 If the preset conditions are met, execute the output module; otherwise, execute the iteration module 207.

[0092] Iteration module 207 is used to process the device loss Qh i The iterative value Qh_itera is obtained by substituting it into the preset iterative optimization algorithm, and the current temperature T of the elastic wave device is calculated based on the iterative value. i =Qh_itera×R, and simultaneously set i=i+1, then return to the judgment module 206;

[0093] Output module 208 is used to output the elastic wave device at temperature T. i-1 The device loss Qh i and admittance Y i As a result of temperature characteristic simulation.

[0094] The temperature characteristic iterative simulation system 200 of the elastic wave device can implement the steps in the temperature characteristic iterative simulation method of the elastic wave device in the above-described embodiments and achieve the same technical effects. Refer to the descriptions in the above-described embodiments, which will not be repeated here.

[0095] The embodiment of the present application further provides a computer device, please refer to Figure 8, Figure 8 is the structure schematic diagram of the computer device provided by the embodiment of the present application, the computer device 300 includes: memory 302, processor 301 and computer program stored in the memory 302 and can run on the processor 301.

[0096] The processor 301 calls the computer program stored in the memory 302 to execute the steps in the temperature characteristic iterative simulation method of the elastic wave device provided by the embodiment of the present application, please combine Figure 1, which specifically includes the following steps:

[0097] S101: Establish a two-dimensional model of an elastic wave device.

[0098] S102: Modify the two-dimensional model, increase the material parameters of the elastic wave device in the parameters of the two-dimensional model, and obtain a characteristic two-dimensional model.

[0099] Step S102 specifically includes:

[0100] The thermal expansion coefficient of the two-dimensional model is modified, and α i (T) represents the corresponding thermal expansion coefficient of the elastic wave device at the working temperature T, and α i (T0) represents the corresponding thermal expansion coefficient of the elastic wave device at the ambient temperature T0, which satisfies the following relationship (1):

[0101] Wherein, Both represent constants.

[0102] The elastic constant, piezoelectric constant, dielectric constant and density of the two-dimensional model are modified, and C ijkl (T) represents the elastic constant at the working temperature T, e kij (T) represents the piezoelectric constant at the working temperature T, ε kj (T) represents the dielectric constant at the working temperature T, and ρ(T) represents the density at the working temperature T, which satisfies the following relationship (2):

[0103] Wherein, Both represent the material property coefficients of the elastic wave device.

[0104] S103: Establish a three-dimensional equivalent heat transfer model of the elastic wave device.

[0105] S104: Perform simulation based on the three-dimensional equivalent heat transfer model to obtain an environmental thermal resistance R of the elastic wave device.

[0106] Step S104 is specifically:

[0107] In the three-dimensional equivalent heat transfer model, mark a heat source, obtain a heat generation power Q' of the heat source, perform simulation operation on the three-dimensional equivalent heat transfer model to obtain an average temperature T' of the heat source, and the environmental thermal resistance R satisfies:

[0108] R = T' / Q'.

[0109] S105: Perform simulation on the characteristic two-dimensional model based on the environmental thermal resistance R to obtain a device loss Qh i-1 and an admittance Y i of the elastic wave device at an ambient temperature T i .

[0110] S106: Determine whether a preset condition is met between Qh i and Qh i-1 , if yes, execute step 108; if no, execute step S107. The preset condition is:

[0111] Qh i = Qh i-1 ; or,

[0112] Qh i and Qh i-1 meet a preset relative tolerance; or

[0113] Qh i and Qh i-1 meet a preset absolute tolerance.

[0114] S107: Substitute the device loss Qh i into a preset iterative optimization algorithm to obtain an iterative value Qh_itera, calculate a current temperature T i of the elastic wave device according to the iterative value, simultaneously set i = i + 1, and return to step S105.

[0115] The preset iterative optimization algorithm is a Newton iteration method, a gradient is defined as grad_Qh, a Newton step size is step_size_newton, a preset step size is step_size, a device loss is Qh i , an iterative value is Qh_itera, and the current temperature T i satisfies the following relationship: grad_Qh = (Qh_itera - Qhi ) / Qh i ; step_size_newton = min(abs(step_size), abs(Qh i / grad_Qh)); Qh_itera = Qh_itera - step_size_newton * grad_Qh; T i = R * Qh_itera;

[0116] Wherein, min is the minimum function, and abs is the absolute value function.

[0117] S108: output the device loss Qh i-1 and admittance Y i of the elastic wave device at temperature T i as the temperature characteristic simulation result.

[0118] The computer device 300 provided by the embodiment of the present application can realize the steps in the temperature characteristic iterative simulation method of the elastic wave device in the above embodiment, and can realize the same technical effects. Refer to the description in the above embodiment, which will not be repeated here.

[0119] The embodiment of the present application also provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to realize each process and step in the temperature characteristic iterative simulation method of the elastic wave device provided by the embodiment of the present application, and can realize the same technical effects. To avoid repetition, it will not be repeated here.

[0120] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by a computer program instructing related hardware. The program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiment of each method. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM) or a random access memory (RAM) and the like.

[0121] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed, or include elements inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0122] Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, also can be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application essentially or say the part of contribution to the prior art can be embodied in the form of software product, the computer software product is stored in a storage medium (such as ROM / RAM, magnetic disc, optical disc), including a plurality of instructions to make a terminal (may be a mobile phone, computer, server, air conditioner, or network equipment, etc.) executes the method described in various embodiments of the present application.

[0123] The above describes the embodiments of the present application in conjunction with the drawings, the disclosed is only the preferred embodiment of the present application, but the present application is not limited to the above-mentioned specific embodiments, the above-mentioned specific embodiments are only illustrative, but not limited, those skilled in the art can make many forms of equivalent changes without departing from the scope of the present application under the inspiration of the present application, and the claims of the present application.

Claims

1. A method of iterative simulation of temperature characteristics of an elastic wave device, characterized by, The method comprises the following steps: S101: establishing a two-dimensional model of an elastic wave device; S102: modifying the two-dimensional model, adding material parameters of the elastic wave device to parameters of the two-dimensional model, to obtain a characteristic two-dimensional model; S103: establishing a three-dimensional equivalent heat transfer model of the elastic wave device; S104: performing simulation based on the three-dimensional equivalent heat transfer model to obtain an environmental thermal resistance R of the elastic wave device; S105: based on the environmental thermal resistance R, simulating the characteristic two-dimensional model to obtain device loss Qh and admittance Y of the elastic wave device at the environmental temperature T i-1 i i ​​​ S106: Determine whether a preset condition is met between Qh i and Qh i-1 , if yes, execute step 108; if no, execute step S107; S107: calculating the device loss Qh i The preset iterative optimization algorithm is substituted to obtain an iterative value Qh_itera, and a current temperature T of the elastic wave device is calculated according to the iterative value i = Qh_itera x R, and meanwhile, i = i + 1, returning to step S105. S108: outputting the device loss Qh and admittance Y of the elastic wave device at temperature T i-1 as the temperature characteristic simulation results. i i ​​ 2. The method of Claim 1, wherein, The preset iterative optimization algorithm is Newton iteration method, the gradient is defined as grad_Qh, the Newton step size is step_size_newton, the preset step size is step_size, the device loss is Qh i , the iteration value is Qh_itera, and the current temperature T i satisfies the following relationship: grad_Qh=(Qh_itera-Qh i ) / Qh i ; step_size_newton=min(abs(step_size), abs(Qh i / grad_Qh)); Qh_itera=Qh_itera-step_size_newton×grad_Qh; T i =R×Qh_itera; Wherein, min is a minimum value function, and abs is an absolute value function.

3. The method of Claim 1, wherein, The preset condition is: Qh i == Qh i-1 ; or, Qh i between Qh i-1 a preset relative tolerance is met; or Qh i between Qh i-1 a preset absolute tolerance is satisfied.

4. The method of Claim 1, wherein, Step S102 is specifically: modifying a coefficient of thermal expansion of the two-dimensional model, defining a i (T) represents a coefficient of thermal expansion corresponding to the elastic wave device at an operating temperature T, a i (T0) represents a coefficient of thermal expansion corresponding to the elastic wave device at an ambient temperature T0, which satisfies the following relation (1): wherein Both represent constants; modifying the elastic constants, piezoelectric constants, dielectric constants, and density of the two-dimensional model, defining C ijkl (T) represents the elastic constant at the operating temperature T, e kij (T) represents the piezoelectric constant at the operating temperature T, ε kj (T) represents the dielectric constant at the operating temperature T, and p(T) represents the density at the operating temperature T, which satisfy the following relation (2): wherein Both represent material property coefficients of the elastic wave device.

5. The method of Claim 1, wherein, Step S104 is specifically: Marking a heat source in the three-dimensional equivalent heat transfer model, obtaining a heat generation power Q' of the heat source, performing simulation operation on the three-dimensional equivalent heat transfer model to obtain an average temperature T' of the heat source, and the environmental thermal resistance R satisfies: R = T' / Q'.

6. A temperature characteristic iterative simulation system of an elastic wave device, characterized by, Comprise: A two-dimensional modeling module for establishing a two-dimensional model of an elastic wave device; A heat conversion module for modifying the two-dimensional model, adding material parameters of the elastic wave device to parameters of the two-dimensional model, to obtain a characteristic two-dimensional model; A three-dimensional modeling module for establishing a three-dimensional equivalent heat transfer model of the elastic wave device; A three-dimensional simulation module for performing simulation based on the three-dimensional equivalent heat transfer model to obtain an environmental thermal resistance R of the elastic wave device; a two-dimensional simulation module configured to simulate the characteristic two-dimensional model based on the environmental thermal resistance R to obtain a device loss Qh and an admittance Y of the elastic wave device at an environmental temperature T i-1 i and an admittance Y i ​​ a judging module, configured to judge whether a preset condition is met between Qh i and Qh i-1 , and if yes, execute the output module; If not, execute the iteration module; an iteration module for calculating the device loss Qh i The iteration value Qh_itera is calculated by substituting the preset iteration optimization algorithm, and the current temperature T of the elastic wave device is calculated according to the iteration value i = Qh_itera x R, and i is set to i+1, and the judgment module is returned. The output module is used to output the elastic wave device at temperature T. i-1 The device loss Qh i and admittance Y i As a result of temperature characteristic simulation.

7. The temperature characteristic iterative simulation system of the elastic wave device according to claim 6, wherein The preset iterative optimization algorithm is Newton iteration method, the gradient is defined as grad_Qh, the Newton step size is step_size_newton, the preset step size is step_size, the device loss is Qh i , the iteration value is Qh_itera, and the current temperature T i satisfies the following relationship: grad_Qh=(Qh_itera-Qh i ) / Qh i ; step_size_newton=min(abs(step_size), abs(Qh i / grad_Qh)); Qh_itera=Qh_itera-step_size_newton×grad_Qh; T i =R×Qh_itera; Wherein, min is a minimum value function, and abs is an absolute value function.

8. The temperature characteristic iterative simulation system of the elastic wave device according to claim 6, wherein The preset condition is: Qh i == Qh i-1 ; or, Qh i between Qh i-1 a preset relative tolerance is satisfied; or Qh i between Qh i-1 a preset absolute tolerance is satisfied.

9. A computer device, comprising: Comprise: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the temperature characteristic iterative simulation method of the elastic wave device according to any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer program is stored on the computer readable storage medium, and the computer program is executed by the processor to implement the steps in the temperature characteristic iterative simulation method of the elastic wave device according to any one of claims 1-5.

Images