Multi-target evaluation method of module power supply radiator based on analytic hierarchy process

Abstract

The invention provides an analytic hierarchy process-based multi-target evaluation method for a module power supply radiator. The method comprises the following steps of: determining structure influence factors of the module power supply radiator according to an analytic hierarchy process; performing expert scoring on the structure influence factors, and determining a weight vector based on expert scoring; establishing a finite element simulation model of the module power supply comprising the radiator; based on the finite element simulation model and a thermosetting coupling analysis method, determining result data of the structure influence factors; determining the entropy weight of each structure influence factor according to the result data of the structure influence factors; based on the weight vector and the entropy weight of each structure influence factor, determining a comprehensive weight corresponding to each structure influence factor; and according to the comprehensive weight of each structure influence factor, comprehensive scores of the radiators of different specifications are calculated, and the radiator corresponding to the highest comprehensive score is the optimal radiator required by the module power supply. According to the scheme, different radiator structures are scored, and the reliability of the radiator structures is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of power supply heat dissipation, and in particular relates to a multi-objective evaluation method for a module power supply heat sink based on hierarchical analysis. Background Art

[0002] With technological advancements, the electronics industry is increasingly demanding lightweight and efficient modular power supply systems. Heat dissipation is particularly important for applications such as airborne and shipborne applications. As the power of modular power supplies increases, relying solely on the module's structure to dissipate heat is no longer sufficient. The temperature of key heating components can exceed the normal operating temperature range, necessitating the installation of a heat sink.

[0003] Traditional heat sink selection primarily considers whether the temperature meets the operating conditions, ignoring structural changes under the influence of temperature fields. However, modular power supplies are generally small in size, and the changes in various structural components caused by temperature are worthy of attention. Furthermore, in many operating environments, the quality requirements for modular power supplies are more stringent. Heat sink selection based solely on a single factor can lead to increased R&D costs and lower efficiency. Therefore, it is necessary to comprehensively consider multiple factors and evaluate the heat sink structure using a more systematic analysis method. This ensures that the heat sink achieves its cooling objectives while improving structural reliability and saving quality, thus opening up more possibilities for modular power supply design. Summary of the Invention

[0004] The purpose of the embodiments of this specification is to provide a multi-objective evaluation method for module power supply heat sinks based on hierarchical analysis.

[0005] To solve the above technical problems, the embodiments of the present application are implemented in the following ways: The present application provides a multi-objective evaluation method for module power supply heat sinks based on hierarchical analysis, the method comprising: Determine the structural influencing factors of the module power radiator according to the hierarchical analysis method; the structural influencing factors include: temperature, deformation, stress, and weight; Experts score the structural influencing factors and determine the weight vector based on the expert scores; Establish a finite element simulation model of the module power supply including the heat sink; Determine the result data of structural influencing factors based on finite element simulation model and thermal-solid coupling analysis method; According to the result data of the structural influencing factors, the entropy weight of each structural influencing factor is determined; Based on the weight vector and the entropy weight of each structural influencing factor, the comprehensive weight corresponding to each structural influencing factor is determined; According to the comprehensive weight of each structural influencing factor, the comprehensive score of heat sinks of different specifications is calculated. The heat sink with the highest comprehensive score is the optimal heat sink required by the module power supply.

[0006] In one embodiment, determining a weight vector based on expert scoring includes: Construct a judgment matrix based on expert scores; Perform column normalization on the judgment matrix to obtain a column normalized matrix; Perform row average calculation on the column normalized matrix to determine the weight vector.

[0007] In one embodiment, performing row average calculation on the column normalized matrix to determine the weight vector includes: Perform row average calculation on the column normalized matrix to obtain the initial weight vector; Calculate the maximum eigenvalue based on the initial weight vector and judgment matrix; According to the maximum eigenvalue, the consistency index is calculated; According to the consistency index, the consistency ratio is determined; If the consistency ratio is less than the preset threshold, the initial weight vector is used as the weight vector; otherwise, the judgment matrix is adjusted until the consistency ratio is less than the preset threshold.

[0008] In one embodiment, based on a finite element simulation model and a thermo-mechanical coupling analysis method, the result data of the structural influencing factors are determined, including: Import the finite element simulation model into the simulation platform, and set the material properties for each component of the module power supply in the simulation platform; Determine the power loss of key heating components in the module power supply based on material properties; Input the power loss into the steady-state temperature field, set the heat transfer coefficient and temperature environment in the steady-state temperature field, and obtain the temperature distribution result of the module power supply; The temperature distribution results are input into the static structure to determine the result data of the structural influencing factors of the module power supply.

[0009] In one embodiment, determining the entropy weight of each structural influencing factor based on the result data of the structural influencing factors includes: The result data of the structural influencing factors are standardized respectively to obtain the corresponding standardized data; Based on the standardized data, determine the probability distribution of each structural influencing factor; According to the probability distribution of each structural influencing factor, the information entropy corresponding to each structural influencing factor is determined; According to the information entropy of each structural influencing factor, the entropy weight corresponding to each structural influencing factor is determined.

[0010] In one embodiment, the comprehensive scores of radiators of different specifications are calculated based on the comprehensive weights of various structural influencing factors, including: According to the comprehensive weight of each structural influencing factor and the standardized data of each structural influencing factor, the comprehensive score of radiators of different specifications is calculated.

[0011] It can be seen from the technical solution provided in the above embodiments of this specification that this solution: uses the hierarchical analysis method to systematically evaluate the radiator structure, takes thermo-solid coupling as the premise, and through the coupling of temperature field and structural field, can more accurately reflect the temperature rise and deformation of the module power supply when using radiators of different specifications, and use this data as a drive to break through the limitations of subjective evaluation, integrate multiple indicators, and use the entropy weight method for quantitative analysis to more scientifically score different module power radiator structures. The solution with the highest score is the optimal design, so that the radiator can achieve the purpose of heat dissipation while improving the reliability of the structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0013] Figure 1 A flowchart of a multi-objective evaluation method for module power radiators based on hierarchical analysis provided in this application; Figure 2 A schematic diagram of the hierarchical structure of structural influencing factors of the module power heat sink provided in this application. DETAILED DESCRIPTION

[0014] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments derived by those skilled in the art based on the embodiments in this specification without creative effort shall fall within the scope of protection of this specification.

[0015] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0016] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments described herein without departing from the scope or spirit of the present application. Other embodiments will be apparent to those skilled in the art from the present description. The present description and examples are intended to be illustrative only.

[0017] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0019] Reference Figure 1 , which shows a flow chart of a multi-objective evaluation method for a module power radiator based on hierarchical analysis applicable to an embodiment of the present application.

[0020] like Figure 1 As shown in FIG, a multi-objective evaluation method for module power heat sink based on hierarchical analysis can include: S110. Determine structural influencing factors of the module power supply heat sink according to the analytic hierarchy process (AHP); structural influencing factors include: temperature, deformation, stress, and weight.

[0021] Specifically, a heat sink design evaluation system is established, such as Figure 2 As shown in Figure 2, the hierarchical structure of the factors affecting the module power radiator structure determined by AHP is: Target layer: factors affecting radiator structure optimization; Criteria layer: temperature, structure; Factor layer: temperature, deformation, stress, and weight. Temperature is the highest temperature, deformation is the maximum deformation, and stress is the maximum equivalent stress.

[0022] S120. Perform expert scoring on the structural influencing factors, and determine a weight vector based on the expert scoring.

[0023] Among them, based on the expert scoring, the weight vector is determined, including: According to the expert scores, a judgment matrix is constructed; wherein the value of each element in the judgment matrix is: the importance of one factor to the importance of another factor in the factor layer in the hierarchical structure of the factors affecting the module power heat sink structure; Perform column normalization on the judgment matrix to obtain a column normalized matrix; Perform row average calculation on the column normalized matrix to determine the weight vector, including: Perform row average calculation on the column normalized matrix to obtain the initial weight vector; Calculate the maximum eigenvalue based on the initial weight vector and judgment matrix; According to the maximum eigenvalue, the consistency index is calculated; According to the consistency index, the consistency ratio is determined; If the consistency ratio is less than the preset threshold, the initial weight vector is used as the weight vector; otherwise, the judgment matrix is adjusted until the consistency ratio is less than the preset threshold.

[0024] Specifically, experts scored using a 1-9 scale, where 1 represents equal importance, 3 represents slightly important, 5 represents obviously important, 7 represents strongly important, 9 represents extremely important, and 2, 4, 6, and 8 represent intermediate values.

[0025] For example, the following Table 1 is an expert scoring table.

[0026] Table 1 Expert scoring table

[0027] Based on the above Table 1, the judgment matrix for:

[0028] by Taking 1 / 3 in the first column and second row as an example, its meaning is: the importance of deformation to the importance of temperature is 1 / 3, and the meanings of other elements are similar.

[0029] Divide each column element in the judgment matrix by the total sum of the column to obtain a column normalized matrix.

[0030] Perform row average calculation on the column normalized matrix to obtain the initial weight vector , the corresponding initial weight vector is obtained from Table 1 above for: .

[0031] The following consistency test is performed to calculate the maximum eigenvalue :

[0032] in, is the judgment matrix, is the initial weight vector, n is the total number of elements in the structural influencing factors, n =4, i is the number of the element in the structural influencing factor, for example, i =1 indicates temperature, i =2 means deformation, i =3 represents stress, i =4 indicates weight.

[0033] Based on the above Table 1, the corresponding maximum eigenvalue is .

[0034] The consistency index is calculated according to the following formula :

[0035] Based on the above Table 1, the consistency index is .

[0036] The consistency ratio was calculated according to the following formula :

[0037] According to the judgment matrix , RI is the random consistency index of the fourth-order matrix, and its value is 0.9.

[0038] The preset threshold can be set according to actual needs. For example, the preset threshold is 0.1.

[0039] Based on the above Table 1 and RI, the consistency ratio is obtained CR≈0.0441<0.1. After verification, the initial weight vector obtained above is used as the final weight vector. .

[0040] If the obtained CR is ≥ 0.1, the judgment matrix is adjusted until the obtained consistency ratio is less than the preset threshold, and the initial weight vector corresponding to this time is used as the final weight vector.

[0041] S130: Establish a finite element simulation model of the module power supply including the heat sink.

[0042] Specifically, a finite element simulation model of a module power supply including a heat sink is established using modeling software such as SOLIDWORKS. Among them, all key components are included in the finite element simulation model. For example, the finite element simulation model includes: an aluminum alloy housing, a PCB board, a heat sink, key heating elements, pins, bolts and other fasteners, and a fixed support on the bottom surface of the module power supply to simulate the welding and fixing working conditions. It is understandable that small features that do not affect thermal analysis, such as chamfers, small holes, etc., can be removed from the finite element simulation model. Among them, the finite element simulation model can include a heat sink model and a module power supply model. It is understandable that when evaluating the performance of heat sinks of different specifications acting on the module power supply, only the heat sink model in the finite element simulation model can be replaced.

[0043] It is also understandable that weight data among the structural influencing factors can be read according to the finite element simulation model.

[0044] S140, based on finite element simulation models and thermo-structural coupling analysis methods, determine the result data of structural influencing factors, including: Import the finite element simulation model into the simulation platform, and set the material properties for each component of the module power supply in the simulation platform; Determine the power loss of key heating components in the module power supply based on material properties; Input the power loss into the steady-state temperature field, set the heat transfer coefficient and temperature environment in the steady-state temperature field, and obtain the temperature distribution result of the module power supply; The temperature distribution results are input into the static structure to determine the result data of the structural influencing factors of the module power supply.

[0045] Specifically, the analysis method of thermo-solid coupling includes the setting of material properties of each component of the module power supply and the analysis of the steady-state temperature field and static structure.

[0046] The simulation platform can be ANSYS WORKBENCH. The established finite element simulation model is imported into ANSYS WORKBENCH. Material properties are then set for each component of the finite element simulation model based on actual conditions to ensure the integrity and accuracy of the thermal and structural parameters of each material. For example, mechanical and thermal parameters such as thermal conductivity, specific heat capacity, density, and thermal expansion coefficient can be input for aluminum alloy housings, heat sinks, and PCB boards. These parameters can be sourced from manufacturer datasheets or measured values to ensure simulation reliability.

[0047] The finite element simulation model is meshed to obtain a mesh model of the module power supply to determine the spatial distribution accuracy of the heat source in the module power supply in the finite element simulation model. It is understandable that when meshing, it is necessary to select an appropriate mesh type and density.

[0048] Calculate the power loss of key heating components used in module power supply, for example, the power loss of common heating components such as MOS tubes and planar transformers and The calculation formulas are:

[0049]

[0050] in, It is the power consumption of MOS tube when the module power supply is working. is the on-resistance between drain and source in the on-state, is the load current; is the power consumption of the planar transformer when the module is working, is the winding loss, is the core loss.

[0051] For example, a 75W wide voltage input isolated regulated single output DC-DC module power supply with a load current of 3.125A has a power loss of MOS tube. =0.02W, power loss of planar transformer =5.47W.

[0052] The calculated power loss of key heating components is used as the input of the steady-state temperature field to perform temperature field analysis on the module power supply, and ANSYS Steady-State Thermal is used to perform steady-state temperature field simulation calculations.

[0053] In the steady-state temperature field, the heat transfer coefficient and ambient temperature are set, the module power supply is placed in the natural convection condition of air, and the temperature distribution results are read.

[0054] The heat sink design method is applied to module power supplies with heat dissipation requirements, taking into account normal temperature and high temperature working conditions. Therefore, the simulated module power supply working conditions include: high temperature working environment, generally 85°C; normal temperature working environment, generally 25°C.

[0055] The temperature distribution structure obtained above is used as the input of the static structure, and the static structure analysis is performed using ANSYS StaticStructural (ANSYS static structure). The mechanical boundary conditions of the module power supply are set, and the deformation and stress distribution results are read.

[0056] S150. Determine the entropy weight of each structural influencing factor based on the result data of the structural influencing factors, including: The result data of the structural influencing factors are standardized respectively to obtain the corresponding standardized data; Based on the standardized data, determine the probability distribution of each structural influencing factor; According to the probability distribution of each structural influencing factor, the information entropy corresponding to each structural influencing factor is determined; According to the information entropy of each structural influencing factor, the entropy weight corresponding to each structural influencing factor is determined.

[0057] Specifically, the range method is used to standardize the data. Temperature, deformation, stress, and weight are all negative indicators. The standardization formula is:

[0058] in, To standardize the data, For the data to be standardized, i is the number of the element in the structural influencing factor, j These are the structural factors affecting radiators of different specifications; for example Indicates the temperature data in a radiator of specification 1; Elements in structural influencing factors i The maximum value in the corresponding sequence, Elements in structural influencing factors i The minimum value in the corresponding series, where the series is formed by the result data of the structural influencing factors corresponding to radiators of different specifications. For example, It indicates the maximum value of the maximum temperature on the surface of the module power supply obtained by simulation when using heat sinks of different specifications.

[0059] Probability distribution of each structural influencing factor The calculation formula is:

[0060] in, a is the specification and quantity of the radiator. For example, Refers to the probability distribution of temperature.

[0061] Information entropy of each structural influencing factor The calculation formula is:

[0062] For example, Refers to the information entropy of temperature.

[0063] The entropy weight of each structural influencing factor is calculated based on the entropy weight method. The calculation formula is:

[0064] For example, based on Table 1 above, the maximum temperature entropy weight is obtained =23.29%, maximum deformation entropy weight =21.01%, maximum equivalent stress entropy weight =22.12%, weight entropy weight =33.5%.

[0065] S160. Based on the weight vector and the entropy weight of each structural influencing factor, determine the comprehensive weight corresponding to each structural influencing factor:

[0066] in, is the subjective weight ratio, is the objective weight ratio, and The value can be set according to actual needs. For example, The value is 0.3, The value is 0.7.

[0067] For example, based on the above Table 1, we get: =

[0068] =

[0069] =

[0070] =

[0071] S170. Calculate comprehensive scores for heat sinks of different specifications based on the comprehensive weights of various structural influencing factors. The heat sink with the highest comprehensive score is the optimal heat sink required for the module power supply.

[0072] Among them, the comprehensive scores of radiators of different specifications are calculated according to the comprehensive weights of various structural influencing factors, including: the comprehensive scores of radiators of different specifications are calculated according to the comprehensive weights of various structural influencing factors and the standardized data of various structural influencing factors:

[0073] Table 2 shows the comprehensive scores for radiators of different specifications, from Plan A to Plan I. For example, Plan A uses a radiator of specification one, Plan I uses a radiator of specification nine, and so on. Plan A uses a radiator with three teeth, Plan B uses a radiator with six teeth, and so on.

[0074] Table 2 Comprehensive ratings of radiators of different specifications

[0075] In this embodiment, the heat sink corresponding to solution F is the optimal heat sink required by the module power supply.

[0076] The multi-objective evaluation method for module power supply heat sinks based on hierarchical analysis provided in the embodiment of the present application utilizes the hierarchical analysis method to systematically evaluate the heat sink structure. Based on the premise of thermo-solid coupling, through the coupling of temperature field and structural field, it can more accurately reflect the temperature rise and deformation of the module power supply when using heat sinks of different specifications. This data is used as a driving force to break through the limitations of subjective evaluation, integrate multiple indicators, and use the entropy weight method for quantitative analysis to more scientifically score different module power supply heat sink structures. The solution with the highest score is the optimal design, so that the heat sink can achieve the purpose of heat dissipation while improving the reliability of the structure.

[0077] It should be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0078] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

Claims

1. A multi-objective evaluation method for module power radiators based on hierarchical analysis, characterized in that: The method comprises: Determine the structural influencing factors of the module power supply heat sink according to the hierarchical analysis method; the structural influencing factors include: temperature, deformation, stress, and weight; Performing expert scoring on the structural influencing factors, and determining a weight vector based on the expert scoring; Establish a finite element simulation model of the module power supply including the heat sink; Determining result data of the structural influencing factors based on the finite element simulation model and the thermal-solid coupling analysis method; Determining the entropy weight of each structural influencing factor based on the result data of the structural influencing factors; Determining a comprehensive weight corresponding to each of the structural influencing factors based on the weight vector and the entropy weight of each of the structural influencing factors; According to the comprehensive weights of the structural influencing factors, the comprehensive scores of heat sinks of different specifications are calculated, and the heat sink corresponding to the highest comprehensive score is the optimal heat sink required by the module power supply.

2. The method according to claim 1, characterized in that Determining a weight vector based on the expert scoring includes: Constructing a judgment matrix based on the expert scores; Performing column normalization processing on the judgment matrix to obtain a column normalized matrix; Perform row average calculation on the column normalized matrix to determine the weight vector.

3. The method according to claim 2, characterized in that The performing row average calculation on the column normalized matrix to determine the weight vector includes: Performing row average calculation on the column normalized matrix to obtain an initial weight vector; Calculating a maximum eigenvalue according to the initial weight vector and the judgment matrix; Calculating a consistency index based on the maximum eigenvalue; determining a consistency ratio according to the consistency index; If the consistency ratio is less than a preset threshold, the initial weight vector is used as the weight vector; otherwise, the judgment matrix is adjusted until the consistency ratio is less than the preset threshold.

4. The method according to claim 1, wherein The result data of the structural influencing factors determined based on the finite element simulation model and the thermal-solid coupling analysis method include: Importing the finite element simulation model into a simulation platform, and setting material properties for various components of the modular power supply in the simulation platform; determining the power loss of key heating components in the module power supply based on the material properties; Inputting the power loss into a steady-state temperature field, and setting the heat transfer coefficient and the temperature environment in the steady-state temperature field to obtain a temperature distribution result of the module power supply; The temperature distribution result is input into a static structure to determine result data of structural influencing factors of the module power supply.

5. The method according to claim 1, wherein Determining the entropy weight of each structural influencing factor based on the result data of the structural influencing factors includes: Standardizing the result data of the structural influencing factors respectively to obtain corresponding standardized data; Determining a probability distribution of each of the structural influencing factors based on the standardized data; Determining the information entropy corresponding to each of the structural influencing factors according to the probability distribution of each of the structural influencing factors; According to the information entropy of each of the structural influencing factors, the entropy weight corresponding to each of the structural influencing factors is determined.

6. The method according to claim 5, characterized in that The comprehensive scores of radiators of different specifications are calculated based on the comprehensive weights of the structural influencing factors, including: According to the comprehensive weights of the structural influencing factors and the standardized data of the structural influencing factors, the comprehensive scores of radiators of different specifications are calculated.

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