Method for optimizing mechanical properties of thermoelectric device

Abstract

The invention discloses a method for optimizing mechanical properties of a thermoelectric device. The method comprises the following steps: determining influence factors for quantitative evaluation based on a single-factor test according to measurement indexes of the mechanical properties of the thermoelectric device; according to all interactions among the influence factors, quantitative interactions required by an orthogonal test are determined; for the influence factors and the quantitative interaction, compiling a multi-factor two-level orthogonal test scheme by using a two-level orthogonal table and an interaction table, performing variance analysis, and determining a target influence factor and a target interaction for further quantitative evaluation; compiling a multi-factor three-level orthogonal test scheme by using a three-level orthogonal table and a corresponding interaction table and carrying out variance analysis on the multi-factor three-level orthogonal test scheme for the target influence factor and the target interaction which are subjected to further quantitative evaluation, and calculating an index average value of a multi-factor level; and optimizing design parameters of the thermoelectric device according to the variance analysis and the index average value.

Description

Technical Field

[0001] The present invention relates to the field of thermoelectric device design, and particularly to an optimization method for the mechanical properties of thermoelectric devices. Background Art

[0002] Thermoelectric conversion technology can directly convert thermal energy into electrical energy, and has the advantages of no moving parts, no noise, no pollution, long service life, etc., and has been widely applied in fields such as deep space exploration and waste heat recovery. In the past few decades, through the efforts of researchers, the performance of a batch of new thermoelectric materials and devices such as skutterudites, SnSe, half-Heuslers, and GeTe has been continuously improved.

[0003] However, for the application of thermoelectric devices, only high energy conversion efficiency is not enough. Thermoelectric devices usually serve under large temperature differences, and at this time, the thermal stress caused by the mismatch of thermal expansion coefficients will accelerate the performance decay and even lead to device failure. In order to reduce thermal stress, various structural optimizations have been applied to the design of thermoelectric devices.

[0004] The structural parameters and material property parameters are the two most important aspects for the optimization of the mechanical properties of thermoelectric devices. In practical applications, both the structural parameters and material property parameters have complex interactive effects on thermal stress. The existing research mainly uses the method of single-factor experiments to optimize the mechanical properties of thermoelectric devices. These studies ignore the interactive effects between various influencing factors, and the obtained optimization schemes have great limitations and are difficult to guide the actual optimization design of the mechanical properties of thermoelectric devices. Summary of the Invention

[0005] In view of the above problems, the present invention provides an optimization method for the mechanical properties of thermoelectric devices, which can effectively reduce the stress level in the device, thereby improving the mechanical stability and service life of thermoelectric devices.

[0006] In a first aspect of the present invention, there is provided an optimization method for the mechanical properties of thermoelectric devices, including: Constructing a three-dimensional finite element model of a thermoelectric device by using ABAQUS software, and determining the influencing factors for quantitative evaluation based on single-factor experiments according to the measurement index of the mechanical properties of the thermoelectric device; wherein the influencing factors include structural parameters and material property parameters, and the measurement index is the maximum first principal stress of the thermoelectric material; Determining the quantitative interactions required for orthogonal experiments according to all the interactions between the influencing factors; For the influencing factors and quantitative interactions, using a two-level orthogonal table and an interaction table to compile a two-level orthogonal experiment scheme for multiple factors and perform variance analysis to determine the target influencing factors and target interactions for further quantitative evaluation; For the target influencing factors and target interactions for the further quantitative evaluation, a multi-factor three-level orthogonal test scheme is compiled using a three-level orthogonal table and the corresponding interaction table, and an analysis of variance is performed. The average values of the indicators for the multi-factor levels are calculated, and the design parameters of the thermoelectric device are optimized based on the analysis of variance and the average values of the indicators.

[0007] In an alternative embodiment, when constructing a three-dimensional finite element model of the thermoelectric device using ABAQUS software, a linear elastic constitutive model is used for the ceramic plate in the thermoelectric device, and an elastoplastic constitutive model is used for the metal material in the thermoelectric device. The constitutive model of the thermoelectric material in the thermoelectric device is adjusted based on the measurement data.

[0008] In an alternative embodiment, the single-factor tests include: Single-factor tests are performed for each influencing factor, and all other influencing factors are kept unchanged when performing the single-factor tests.

[0009] In an alternative embodiment, all the interactions between the influencing factors: All the interactions between the influencing factors, determining the quantitative interactions required for the orthogonal test, include: In two different value environments of the first influencing factor, if there are different influencing trends of the second influencing factor on the measurement index, it is determined that the first influencing factor and the second influencing factor are the quantitative interactions required for the orthogonal test.

[0010] In an alternative embodiment, the compilation of a multi-factor two-level orthogonal test scheme using a two-level orthogonal table and the corresponding interaction table and the performance of an analysis of variance include: Determine the columns occupied by each influencing factor and interaction according to the two-level orthogonal table and the corresponding interaction table, and compile a multi-factor two-level orthogonal test scheme; Establish a model using the finite element method, and implement the multi-factor two-level orthogonal test scheme based on the model; Calculate the variance ratios of the target influencing factors in the multi-factor two-level orthogonal test using the analysis of variance method, and obtain the confidence level and influence degree of each target influencing factor according to the distribution table of the variance ratios.

[0011] In an alternative embodiment, the compilation of a multi-factor three-level orthogonal test scheme using a three-level orthogonal table and the corresponding interaction table and the performance of an analysis of variance, and the calculation of the average values of the indicators for each factor level, include: Determine the columns occupied by each target influencing factor and target interaction according to the three-level orthogonal table and the corresponding interaction table, and compile a multi-factor three-level orthogonal test scheme; Establish a model using the finite element method, and implement the multi-factor three-level orthogonal test scheme based on the model; The variance ratio of each influencing factor in a multi-factor three-level orthogonal experiment is calculated by the analysis of variance method, and the confidence level and influence degree of each target influencing factor are obtained according to the distribution table of the variance ratio. For each measurement index, the average value of the factor levels of each target influencing factor in the multi-factor three-level orthogonal experiment is calculated by the range analysis method.

[0012] In an alternative embodiment, obtaining the confidence level and influence degree of each target influencing factor includes: The confidence levels of each target influencing factor are arranged in ascending order, and the order of importance of each target influencing factor is determined according to the arrangement order.

[0013] In an alternative embodiment, the design parameters of the thermoelectric device are sequentially determined according to the order of importance of each target influencing factor, and each design parameter is determined as the factor level corresponding to the minimum value among the index average values corresponding to the target influencing factor in the multi-factor three-level orthogonal experiment.

[0014] In an alternative embodiment, the design parameters of the thermoelectric device are sequentially determined according to the order of importance of each influencing factor, and each design parameter is determined as the factor level corresponding to the minimum value among the average values of each factor level of this influencing factor in the multi-factor three-level orthogonal experiment.

[0015] In an alternative embodiment, the structural parameters include: ceramic plate thickness, electrode thickness, barrier layer thickness, thermoelectric arm fillet radius, thermoelectric arm spacing in the X direction, and thermoelectric arm spacing in the Y direction.

[0016] In an alternative embodiment, the material property parameters include thermal conductivity, thermal expansion coefficient, elastic modulus, and yield strength.

[0017] The present invention uses an orthogonal analysis method to analyze the interaction effects between influencing factors, which can conveniently optimize the design of thermoelectric devices and reduce the failure risk caused by thermal stress during the use of thermoelectric devices.

[0018] By analyzing the influence of each material property parameter on the mechanical properties in the thermoelectric device, the present invention can help obtain optimized replacement materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flowchart for optimizing the mechanical properties of the thermoelectric device in the present invention.

[0020] Figure 2 It is a schematic diagram of the modeling of the thermoelectric device in the embodiment of the present invention.

[0021] Figure 3Schematic diagram of the single-factor experiment results of the structural parameters in the embodiments of the present invention.

[0022] Figure 4 Schematic diagram of the interaction of the structural parameters in the embodiments of the present invention.

[0023] Figure 5 Schematic diagram of the influence trend of the structural parameters on the stress in the embodiments of the present invention.

[0024] Figure 6 Schematic diagram of the interaction between the significantly influential structural parameters in the embodiments of the present invention.

[0025] Figure 7 Schematic diagram of the single-factor experiment results of the material property parameters in the embodiments of the present invention.

[0026] Figure 8 Schematic diagram of the combination of the material property parameters with obvious interaction in the embodiments of the present invention.

[0027] Figure 9 Schematic diagram of the combination of the material property parameters with almost no interaction in the embodiments of the present invention.

[0028] Figure 10 Schematic diagram of the influence trend of the material property parameters on the stress in the embodiments of the present invention.

[0029] Figure 11 Schematic diagram of the interaction between the significantly influential material property parameters in the embodiments of the present invention.

[0030] Figure 12 Schematic diagram of the comparison of the first principal stress distributions of the thermoelectric materials in different models in the embodiments of the present invention. Detailed implementation manners

[0031] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts fall within the protection scope of the present invention.

[0032] It should be understood that the terms "first", "second", "third", etc. in the claims, the description and the drawings of the present disclosure are used to distinguish different objects, rather than to describe a specific order. The terms "including" and "comprising" used in the description and claims of the present disclosure indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0033] Please refer toFigure 1 , the present invention provides an optimization method for the mechanical properties of a thermoelectric device, including the following steps.

[0034] Step 100: Use ABAQUS software (ABAQUS is mainly used for finite element analysis in fields such as structural mechanics, heat conduction, fluid dynamics, and multi-physics coupling) to construct a three-dimensional finite element model of the thermoelectric device, and determine the influencing factors for quantitative evaluation based on single-factor experiments according to the measurement indicators of the mechanical properties of the thermoelectric device.

[0035] In an embodiment of the present invention, the influencing factors include structural parameters and material property parameters, and the measurement indicator is the maximum first principal stress at the high-temperature end and the low-temperature end of the thermoelectric material.

[0036] When using ABAQUS software to construct a three-dimensional finite element model of the thermoelectric device, a linear elastic constitutive model is used for the ceramic plate in the thermoelectric device, and an elastoplastic constitutive model is used for the metal material in the thermoelectric device. Adjust the constitutive model of the thermoelectric material in the thermoelectric device according to the measurement data; as Figure 2 shown, construct a thermoelectric device combining N-type thermoelectric material and P-type thermoelectric material.

[0037] Then, conduct single-factor experiments for each influencing factor. When conducting single-factor experiments, all other influencing factors remain unchanged.

[0038] Step 200: Determine the quantitative interaction required for the orthogonal experiment according to all the interactions between the influencing factors.

[0039] In an embodiment of the present invention, in two different value environments of the first influencing factor, if there is a different influence trend of the second influencing factor on the measurement indicator, it is determined that the first influencing factor and the second influencing factor are the quantitative interactions required for the orthogonal experiment.

[0040] Step 300: For the influencing factors and quantitative interactions, use a two-level orthogonal table and an interaction table to compile a two-level orthogonal experiment plan for multiple factors and conduct variance analysis to determine the target influencing factors and target interactions for further quantitative evaluation.

[0041] In an embodiment of the present invention, determine the columns occupied by each influencing factor and interaction according to the two-level orthogonal table and the corresponding interaction table, and compile a two-level orthogonal experiment plan for multiple factors; establish a model using the finite element method and implement the two-level orthogonal experiment plan for multiple factors based on the model; use the variance analysis method to calculate the variance ratio of each target influencing factor in the two-level orthogonal experiment for multiple factors, and obtain the confidence level and influence degree of each target influencing factor according to the distribution table of the variance ratio.

[0042] Step 400: For the target influencing factors and target interactions obtained from the further quantitative evaluation, use a three-level orthogonal array and the corresponding interaction array to formulate a multi-factor three-level orthogonal experiment plan, conduct an analysis of variance, calculate the average values of the indicators for the multi-factor levels, and optimize the design parameters of the thermoelectric device based on the analysis of variance and the average values of the indicators.

[0043] In an embodiment of the present invention, the steps of using a three-level orthogonal array and the corresponding interaction array to formulate a multi-factor three-level orthogonal experiment plan, conduct an analysis of variance, and calculate the average values of the indicators for each factor level include: Determine the columns occupied by each target influencing factor and target interaction according to the three-level orthogonal array and the corresponding interaction array, and formulate a multi-factor three-level orthogonal experiment plan; establish a model using the finite element method, and implement the multi-factor three-level orthogonal experiment plan based on the model; calculate the variance ratios of the influencing factors in the multi-factor three-level orthogonal experiment using the analysis of variance method, and obtain the confidence levels and influence degrees of each target influencing factor according to the distribution table of the variance ratios; for each measurement index, calculate the average values of the factor levels of each target influencing factor in the multi-factor three-level orthogonal experiment using the range analysis method.

[0044] Arrange the confidence levels of each target influencing factor in ascending order, and determine the importance order of each target influencing factor according to the arrangement order.

[0045] The design parameters of the thermoelectric device are determined in turn according to the importance order of each target influencing factor, and each design parameter is determined as the factor level corresponding to the minimum value among the average values of the indicators corresponding to the target influencing factors in the multi-factor three-level orthogonal experiment.

[0046] Among them, the structural parameters include: the thickness of the ceramic plate, the thickness of the electrode, the thickness of the barrier layer, the fillet radius of the thermoelectric arm, the spacing of the thermoelectric arm in the X direction, and the spacing of the thermoelectric arm in the Y direction. The material property parameters include thermal conductivity, coefficient of thermal expansion, elastic modulus, and yield strength.

[0047] The present invention uses the orthogonal analysis method to analyze the interaction effects between influencing factors, which can conveniently optimize the design of the thermoelectric device and reduce the failure risk caused by thermal stress during the use of the thermoelectric device.

[0048] By analyzing the influence of each material property parameter in the thermoelectric device on the mechanical properties, the present invention can help obtain optimized replacement materials.

[0049] Embodiment 1 Taking the structural optimization of the mechanical properties of the thermoelectric device as an example, it further illustrates how to optimize the mechanical properties of the thermoelectric device.

[0050] Figure 2Schematic diagram for modeling the thermoelectric device of this embodiment. Different material property parameters and structural parameters are predefined according to the actual situation of the thermoelectric device to meet the need for 1:1 scale modeling of the thermoelectric device. The C3D8T element in the ABAQUS software is used to simulate the entire device structure, and this element has functions of heat transfer, stress-strain, and thermal stress simulation.

[0051] When applying loads, according to the actual installation conditions of the thermoelectric device: the low-temperature end is fixed and constrained, and a normal pressure of 2 MPa is applied to the high-temperature end. The temperatures of the high-temperature end and the low-temperature end are set to 300 K and 900 K respectively. All heat convection, heat radiation, and contact thermal resistance are ignored in the model.

[0052] The considered structural parameters include: the thickness of the ceramic plate, the thickness of the electrode, the thickness of the barrier layer, the fillet radius of the thermoelectric arm, the spacing of the thermoelectric arms in the X direction, and the spacing of the thermoelectric arms in the Y direction. Figure 3 are the single-factor experimental results of each structural parameter. It can be seen that the spacing of the thermoelectric arms in the Y direction has almost no influence on the stress, so this structural parameter will be ignored in the subsequent orthogonal experiment. Figure 4 are the schematic diagrams of the interaction effects of 5 structural parameters. a1 to h1 are the schematic diagrams of the interaction effects of the stress at the high-temperature end, and a2 to h2 are the schematic diagrams of the interaction effects of the stress at the low-temperature end. Among the 10 groups of factor combinations in the figure, there are only three groups of structural parameters with obvious interaction effects: the thickness of the ceramic plate and the fillet radius, the thickness of the electrode and the fillet radius, and the thickness of the ceramic plate and the thickness of the electrode.

[0053] Design a three-level orthogonal experiment according to the obtained influencing factors and interaction effects. According to Figure 3 The levels of each factor determined by the single-factor experimental results are shown in Table 1, and the orthogonal table of the three-level orthogonal experiment designed according to the interaction Table 2 is shown in Table 3.

[0054] Table 1 Factor-level table for the orthogonal experiment of structural parameters Table 2 Interaction table of the L 27 (3 13 ) orthogonal table Table 3 Design of the L 27 (3 13 ) orthogonal table for the orthogonal experiment of structural factors The present invention defines a measurement index for the mechanical failure of the thermoelectric device. The measurement index is the maximum value of the first principal stress at the high-temperature end and the low-temperature end of the thermoelectric material. The results of the orthogonal experiment are shown in Table 4.

[0055] Table 4 Results of the orthogonal experiment of structural factors For each measurement index (hereinafter referred to as index), the average value of the index of each factor level in the influencing factor column of the multi-factor three-level orthogonal table is calculated using the range analysis method. The influence trends of each factor (factors A, B, C, D, and E in Table 1) on the index are as Figure 5 , that is, the influence trend on the maximum stress.

[0056] For each index, the variance ratio of each influencing factor and interaction in the multi-factor three-level orthogonal table is calculated using the analysis of variance method. The confidence level and influence degree of each factor and interaction are obtained according to the variance ratio distribution table. In this embodiment, 0.01 and 0.05 are used as the boundaries to determine the significance level of the influencing factors. The significance levels of each influencing factor and interaction are shown in Table 5. In Table 5, ⊕ represents the interaction. The interactions between the structural factors with relatively significant influences are shown in Figure 6 : the fillet radius and the electrode thickness, the ceramic plate thickness and the electrode thickness.

[0057] Table 5 Variance Analysis of Orthogonal Test of Structural Factors According to the influence trends and significance rankings of each structural factor, each structural parameter is confirmed as follows: the X-direction spacing of the thermoelectric arm is 1 mm; the electrode thicknesses at the high-temperature end and the low-temperature end are 2.3 mm and 1.3 mm respectively; the barrier layer thicknesses at the high-temperature end and the low-temperature end are 0.05 mm and 0.45 mm respectively; the ceramic plate thicknesses at the high-temperature end and the low-temperature end are 0.3 mm and 0.6 mm respectively.

[0058] Example 2 Taking the material combination optimization of the mechanical properties of the thermoelectric device as an example, this embodiment further illustrates how to formulate an optimization strategy.

[0059] The specific process, modeling method, boundary conditions, and analysis indexes of this embodiment are the same as those of Example 1. To perform the material combination optimization design of the thermoelectric device, it is necessary to examine the influence of all material property parameters on the indexes.

[0060] The material property parameters used in the thermo-mechanical coupling model include thermal conductivity, coefficient of thermal expansion, elastic modulus, and yield strength. These property parameters belong to (a) ceramic plate, (b) barrier layer, and (c) electrode respectively. The single-factor test results of the material property parameters are shown in Figure 7 . It can be seen that only 6 material property parameters have obvious influences on the results, and they are: the coefficient of thermal expansion of the high-temperature end ceramic plate, the coefficient of thermal expansion of the high-temperature end barrier layer, the coefficient of thermal expansion of the high-temperature end electrode, the yield strength of the high-temperature end barrier layer, the yield strength of the high-temperature end electrode, and the elastic modulus of the low-temperature end electrode.

[0061] Figure 8 And Figure 9 are the interactions of the 6 material property parameters, among whichFigure 8 The indexes of a1 to g1 are the high-temperature-end stresses, and the indexes of a2 to g2 are the low-temperature-end stresses; Figure 9 The indexes of a1 to h1 are the high-temperature-end stresses, and the indexes of a2 to h2 are the low-temperature-end stresses. Among the 15 groups of factor combinations formed by 6 material property parameters, only seven groups of material property parameter combinations have obvious interaction effects (stress crossovers), and they are respectively: the thermal expansion coefficient of the high-temperature-end ceramic plate and the thermal expansion coefficient of the high-temperature-end electrode, the thermal expansion coefficient of the high-temperature-end ceramic plate and the thermal expansion coefficient of the high-temperature-end barrier layer, the thermal expansion coefficient of the high-temperature-end electrode and the thermal expansion coefficient of the high-temperature-end barrier layer, the thermal expansion coefficient of the high-temperature-end ceramic plate and the yield strength of the high-temperature-end electrode, the thermal expansion coefficient and the yield strength of the high-temperature-end electrode, the thermal expansion coefficient of the high-temperature-end barrier layer and the yield strength of the high-temperature-end electrode, the thermal expansion coefficient and the yield strength of the high-temperature-end barrier layer.

[0062] Since there are many material property parameters and interaction effects to be considered, a two-level orthogonal test scheme needs to be compiled to obtain the target influencing factors and target interaction effects with greater significance.

[0063] According to Figure 7 The factor levels determined by the single-factor test results are shown in Table 6, and the orthogonal table of the two-level orthogonal test designed according to the interaction table 7 is shown in Table 8.

[0064] Table 6 Factor level table for screening orthogonal test Table 7 Interaction table of L 16 (2 15 ) Interaction table of orthogonal table Table 8 Design of L 16 (2 15 ) Orthogonal table design The present invention defines a measurement index for the mechanical failure of a thermoelectric device, and the measurement index is the maximum value of the first principal stress at the high-temperature end and the low-temperature end of the thermoelectric material. The results of the orthogonal test are shown in Table 9.

[0065] Table 9 Results of screening orthogonal test For each measurement index, the variance ratio of each influencing factor and interaction effect in the multi-factor three-level orthogonal table is calculated by using the analysis of variance method, and the confidence level and influence degree of each factor and interaction effect are obtained according to the variance ratio distribution table. In this embodiment, the significance level of the influencing factors is determined with 0.01 and 0.05 as the boundaries, and the significance levels of the influencing factors and interaction effects with the high-temperature-end stress and the low-temperature-end stress as the analysis indexes are shown in Table 10 and Table 11 respectively.

[0066] Analysis of Variance of Screening Orthogonal Experiment with High-temperature End Stress as Index Analysis of Variance of Screening Orthogonal Experiment with Low-temperature End Stress as Index From the screening results, it can be seen that there are obvious differences in the factors and interaction effects that have significant effects on the high-temperature end stress and the low-temperature end stress. Therefore, next, multi-factor three-level orthogonal experiment schemes are prepared respectively with the high-temperature end stress and the low-temperature end stress as indexes for the optimization design of material combinations.

[0067] As can be seen from Table 10, the material property parameters that have significant effects on the high-temperature end stress include: yield strength of the high-temperature end barrier layer, yield strength of the high-temperature end electrode, elastic modulus of the low-temperature end electrode, thermal expansion coefficient of the high-temperature end ceramic plate, and the interaction between the thermal expansion coefficient of the high-temperature end ceramic plate and the thermal expansion coefficient of the high-temperature end barrier layer. In order to fully consider these influencing factors, the three-level orthogonal experiment scheme considers 5 material property parameters: thermal expansion coefficient of the high-temperature end ceramic plate, yield strength of the high-temperature end electrode, thermal expansion coefficient of the high-temperature end barrier layer, yield strength of the high-temperature end barrier layer, elastic modulus of the low-temperature end electrode; and 2 interaction effects: interaction between the thermal expansion coefficient of the high-temperature end ceramic plate and the yield strength of the high-temperature end electrode, interaction between the thermal expansion coefficient of the high-temperature end ceramic plate and the thermal expansion coefficient of the high-temperature end barrier layer.

[0068] According to Figure 7 the results of the single-factor experiment, the factor level table is shown in Table 12.

[0069] Table 12 Factor Level Table of Orthogonal Experiment with High-temperature End Stress as Index The interaction table of the three-level orthogonal table is shown in Table 2. Based on the factor level table and the interaction table, the orthogonal table of the three-level orthogonal experiment with the high-temperature end stress as the index is shown in Table 13.

[0070] Table 13 Orthogonal Table of Orthogonal Experiment with High-temperature End Stress as Index The results of the orthogonal experiment with the high-temperature end stress as the index are shown in Table 14.

[0071] Table 14 Results of Orthogonal Experiment with High-temperature End Stress as Index Similarly, by comparing the stress P values, the material property parameters that have significant effects on the low-temperature end stress mainly include: thermal expansion coefficient of the high-temperature end ceramic plate, yield strength of the high-temperature end electrode, elastic modulus of the low-temperature end electrode, and the interaction between the thermal expansion coefficient of the high-temperature end ceramic plate and the yield strength of the high-temperature end electrode.

[0072] To fully consider these influencing factors, the three-level orthogonal test plan takes into account 5 material property parameters: the thermal expansion coefficient of the ceramic plate at the high-temperature end, the yield strength of the electrode at the high-temperature end, the thermal expansion coefficient of the electrode at the high-temperature end, the yield strength of the barrier layer at the high-temperature end, and the elastic modulus of the electrode at the low-temperature end; as well as 3 interaction effects: the thermal expansion coefficient of the ceramic plate at the high-temperature end and the yield strength of the electrode at the high-temperature end, the yield strength of the electrode at the high-temperature end and the thermal expansion coefficient of the electrode at the high-temperature end, and the thermal expansion coefficient of the ceramic plate at the high-temperature end and the thermal expansion coefficient of the electrode at the high-temperature end.

[0073] According to Figure 7 the results of the single-factor test, the factor level table is shown in Table 15.

[0074] Table 15 Factor level table of the orthogonal test with the low-temperature end stress as the index The interaction table of the three-level orthogonal table is shown in Table 2. Based on the factor level table and the interaction table, the orthogonal table of the three-level orthogonal test with the low-temperature end stress as the index is shown in Table 16.

[0075] Table 16 Orthogonal table of the orthogonal test with the low-temperature end stress as the index The results of the orthogonal test with the low-temperature end stress as the index are shown in Table 17.

[0076] Table 17 Results of the orthogonal test with the high-temperature end stress as the index For each index respectively, the index average values of each factor level in the influencing factor columns of the multi-factor three-level orthogonal table are calculated using the range analysis method, and the influence trends of each factor on the index are as Figure 10 .

[0077] For each index respectively, the variance ratios of each influencing factor and interaction effect in the multi-factor three-level orthogonal table are calculated using the variance analysis method, and the confidence level and influence degree of each factor and interaction effect are obtained according to the variance ratio distribution table. In this embodiment, the significance level of the influencing factors is determined with 0.01 and 0.05 as the boundaries, and the significance levels of each influencing factor and interaction effect are shown in Table 18. In the table, ⊕ represents the interaction effect, and the interaction effects between the structural factors with relatively significant influence are shown in Figure 11 .

[0078] Table 18 Variance analysis of the orthogonal test of material property parameters The interaction effects that have a significant impact on the index are shown in Figure 11 , including the thermal expansion of the barrier layer at the high-temperature end (10 -6 ), and the thermal expansion of the ceramic plate at the high-temperature end (10 -6 ).

[0079] Next, based on the influence trends and significance rankings of the performance parameters of each material on the indicators, the material combination is optimized, that is, the materials are replaced. The performance parameters that have a significant impact on stress belong to 4 materials: the high-temperature ceramic plate, the high-temperature barrier layer, the high-temperature electrode, and the low-temperature electrode.

[0080] For the high-temperature ceramic plate, the influence of the thermal expansion coefficient of the high-temperature ceramic plate on the high-temperature stress is mainly reflected in the interaction with the thermal expansion coefficient of the high-temperature barrier layer, and is opposite to the influence trend on the low-temperature stress. Comparing the P values, the influence of the thermal expansion coefficient of the high-temperature ceramic plate on the low-temperature stress is more significant. Considering the influence on the low-temperature stress first, the ceramic plate at the high temperature is replaced from Al2O3 in the initial model to Si3N4.

[0081] For the high-temperature barrier layer, both the yield strength and the thermal expansion coefficient have a significant impact on stress. Obviously, the high-temperature barrier layer with a lower yield strength is beneficial to reducing both the high-temperature and low-temperature stresses. The influence of the thermal expansion coefficient of the high-temperature barrier layer on stress is reflected in the interaction with the thermal expansion coefficient of the high-temperature ceramic plate, and its significance is lower than that of the yield strength. When the high-temperature ceramic plate is selected as Si3N4, the high-temperature barrier layer can significantly reduce stress only when it is very large (~1.5×10 -5 K -1 ). There is no such material in the barrier layer of the currently used HH device. If the yield strength with greater significance is considered first, the Cr barrier layer at the high temperature can be replaced by Mo.

[0082] For the high-temperature electrode, similar to the high-temperature barrier layer, there are also two performance parameters with significant influence, namely the yield strength and the thermal expansion coefficient. The influence of the yield strength is independent of other performance parameters, and a low yield strength is beneficial to reducing stress. The influence of the thermal expansion coefficient is coupled with the thermal expansion coefficient of the high-temperature ceramic plate, and when the high-temperature ceramic plate is Si3N4, the thermal expansion coefficient has almost no influence on stress. Considering the yield strength first, the Cu electrode at the high temperature can be replaced by Au.

[0083] Only the elastic modulus of the low-temperature electrode has a significant impact on stress, and there is no interaction involved. A lower elastic modulus of the low-temperature electrode is beneficial to reducing stress. Therefore, the Cu electrode at the low temperature can be replaced by Ag.

[0084] Next, compare the calculation results of the initial (see Figure 12 (a) and Figure 12 (b)) and the optimized model to verify the effectiveness of the optimization method described in the present invention.

[0085] According to the optimization solutions obtained in Example 1 and Example 2, models of the optimized structure, models of the optimized material combination, and models combining both were established respectively. The calculated first principal stress distribution of the obtained thermoelectric materials is as Figure 12 .

[0086] Optimization of the material combination (see Figure 12 (e) and Figure 12 (f)) can significantly reduce the stresses at the high-temperature end and the low-temperature end of the thermoelectric material, with the reduction amplitudes being 50% and 20% respectively. Although structural optimization (see Figure 12 (c) and Figure 12 (d)) has no obvious effect on reducing the stress of the thermoelectric material, if it is superimposed with the material combination optimization (see Figure 12 (g) and Figure 12 (h)), the reduction amplitudes of the stresses at the high-temperature end and the low-temperature end can reach 70% and 40% respectively.

[0087] The invention uses the orthogonal analysis method to analyze the interaction effects between factors, which can conveniently optimize the design of thermoelectric devices and reduce the failure risk caused by thermal stress during the use of thermoelectric devices.

[0088] By analyzing the influence of the performance parameters of each material in the thermoelectric device on the mechanical properties, the invention can help obtain optimized replacement materials.

[0089] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. And the scope of the preferred embodiments of the present invention includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in the reverse order according to the involved functions, rather than in the order shown or discussed. This should be understood by those skilled in the technical field to which the embodiments of the present invention belong.

[0090] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An optimization method for the mechanical properties of a thermoelectric device, characterized in that, Including: Construct a three-dimensional finite element model of a thermoelectric device using ABAQUS software, and determine the influencing factors for quantitative evaluation based on single-factor tests according to the measurement indexes of the mechanical properties of the thermoelectric device; Wherein the influencing factors include structural parameters and material property parameters, and the measurement index is the maximum first principal stress of the thermoelectric material; Determine the quantitative interactions required for the orthogonal test according to all the interactions between the influencing factors; For the influencing factors and quantitative interactions, use a two-level orthogonal table and an interaction table to compile a two-level orthogonal test plan for multiple factors and perform variance analysis to determine the target influencing factors and target interactions for further quantitative evaluation; For the target influencing factors and target interactions for further quantitative evaluation, use a three-level orthogonal table and the corresponding interaction table to compile a three-level orthogonal test plan for multiple factors and perform variance analysis, and calculate the index average values of multiple factor levels. Optimize the design parameters of the thermoelectric device according to the variance analysis and the index average values; 2. The optimization method for the mechanical properties of the thermoelectric device according to claim 1, wherein When constructing a three-dimensional finite element model of a thermoelectric device using ABAQUS software, a linear elastic constitutive model is used for the ceramic plate in the thermoelectric device, and an elastoplastic constitutive model is used for the metal material in the thermoelectric device. Adjust the constitutive model of the thermoelectric material in the thermoelectric device according to the measurement data; 3. The optimization method for the mechanical properties of the thermoelectric device according to claim 1, characterized in that, The single-factor test includes: Implement a single-factor test for each influencing factor. When implementing the single-factor test, all other influencing factors remain unchanged; 4. The optimization method for the mechanical properties of the thermoelectric device according to claim 1 or 3, characterized in that All the interactions between the influencing factors, determining the quantitative interactions required for the orthogonal test, include: In two different value environments of the first influencing factor, if there are different influencing trends of the second influencing factor on the measurement index, it is determined that the first influencing factor and the second influencing factor are the quantitative interactions required for the orthogonal test; 5. The optimization method for the mechanical properties of a thermoelectric device according to claim 1, wherein The use of a two-level orthogonal table and the corresponding interaction table to compile a two-level orthogonal test plan for multiple factors and perform variance analysis includes: Determine the columns occupied by each influencing factor and interaction according to the two-level orthogonal table and the corresponding interaction table, and compile a two-level orthogonal test plan for multiple factors; Establish a model using the finite element method and implement a two-level orthogonal test plan for multiple factors based on the model; Use the variance analysis method to calculate the variance ratios of the target influencing factors in the two-level orthogonal test for multiple factors, and obtain the confidence level and influence degree of each target influencing factor according to the distribution table of the variance ratios; 6. The optimization method for the mechanical properties of the thermoelectric device according to claim 1, wherein The use of a three-level orthogonal table and the corresponding interaction table to compile a three-level orthogonal test plan for multiple factors and perform variance analysis, and calculate the index average values of each factor level, includes: Determine the columns occupied by each target influencing factor and target interaction according to the three-level orthogonal table and the corresponding interaction table, and compile a three-level orthogonal test plan for multiple factors; Establish a model using the finite element method and implement a three-level orthogonal test plan for multiple factors based on the model; Use the variance analysis method to calculate the variance ratios of the influencing factors in the three-level orthogonal test for multiple factors, and obtain the confidence level and influence degree of each target influencing factor according to the distribution table of the variance ratios; For each measurement index, the average value of the factor levels of each target influencing factor in the multi-factor three-level orthogonal experiment is calculated using the range analysis method.

7. The optimization method for the mechanical properties of the thermoelectric device according to claim 6, characterized in that, The obtaining of the confidence level and influence degree of each target influencing factor includes: Arrange the confidence levels of each target influencing factor in ascending order, and determine the importance order of each target influencing factor according to the arrangement order.

8. The optimization method for the mechanical properties of the thermoelectric device according to claim 7, characterized in that, The design parameters of the thermoelectric device are determined in turn according to the importance order of each target influencing factor, and each design parameter is determined as the factor level corresponding to the minimum value among the index average values corresponding to the target influencing factors in the multi-factor three-level orthogonal experiment.

9. The optimization method for the mechanical properties of the thermoelectric device according to claim 1, characterized in that The structural parameters include: ceramic plate thickness, electrode thickness, barrier layer thickness, thermoelectric arm fillet radius, thermoelectric arm spacing in the X direction, and thermoelectric arm spacing in the Y direction.

10. The optimization method for the mechanical properties of the thermoelectric device according to claim 1, wherein, The material property parameters include thermal conductivity, thermal expansion coefficient, elastic modulus, and yield strength.

Images