Multi-objective evaluation method for module power radiator based on analytic hierarchy process

Abstract

The application provides a multi-target evaluation method of a module power supply radiator based on analytic hierarchy process, which comprises the following steps: determining structural influence factors of the module power supply radiator according to the analytic hierarchy process; performing expert scoring on the structural influence factors, and determining a weight vector based on the expert scoring; establishing a finite element simulation model of the module power supply including the radiator; determining result data of the structural influence factors based on the finite element simulation model and a thermal-structure coupling analysis method; determining entropy weights of the structural influence factors according to the result data of the structural influence factors; determining comprehensive weights corresponding to the structural influence factors based on the weight vector and the entropy weights of the structural influence factors; and calculating comprehensive scores of different specifications of the radiator according to the comprehensive weights of the structural influence factors, wherein the radiator corresponding to the highest comprehensive score is the optimal radiator required by the module power supply. The scheme scores different radiator structures, thereby improving the reliability of the radiator structure.

Description

Technical Field

[0001] This invention belongs to the field of power supply heat dissipation technology, and specifically relates to a multi-objective evaluation method for modular power supply heat sinks based on hierarchical analysis. Background Technology

[0002] With technological advancements, the electronic field is continuously upgrading its structural requirements for modular power supplies, increasingly demanding lightweight and efficient modular power supply systems. This is especially true in airborne or shipborne applications, where heat dissipation is paramount. As the power of modular power supplies increases, relying solely on the power supply's own structure for heat dissipation is no longer sufficient. The temperatures of critical heat-generating components exceed their normal operating range, necessitating the addition of heat sinks.

[0003] Traditional heat sink selection primarily considers whether the temperature meets the operating conditions, neglecting structural changes under the influence of the temperature field. However, modular power supplies are generally small in size, and the changes in various structural components due to temperature are worth noting. Furthermore, in many operating environments, the quality requirements for modular power supplies are quite stringent. Selecting a heat sink based on only a single factor leads to increased R&D costs and lower efficiency. Therefore, it is necessary to comprehensively consider multiple factors and use a more systematic analytical approach to evaluate the heat sink structure. This allows the heat sink to achieve its heat dissipation purpose while improving structural reliability, saving weight, and providing more possibilities for modular power supply design. Summary of the Invention

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

[0005] To solve the above-mentioned technical problems, the embodiments of this application are implemented in the following ways:

[0006] This application provides a multi-objective evaluation method for modular power supply heat sinks based on hierarchical analysis, the method comprising:

[0007] The structural influencing factors of the modular power supply heat sink were determined using the analytic hierarchy process (AHP). These factors included temperature, deformation, stress, and weight.

[0008] The structural influencing factors are scored by experts, and the weight vector is determined based on the expert scores;

[0009] Establish a finite element simulation model of the modular power supply, including the heat sink;

[0010] Based on the finite element simulation model and the thermo-structure coupling analysis method, the results data of structural influencing factors were determined.

[0011] Based on the results data of structural influencing factors, determine the entropy weight of each structural influencing factor;

[0012] 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;

[0013] Based on the comprehensive weight of each structural influencing factor, the comprehensive score of heat sinks of different specifications is calculated, and the heat sink with the highest comprehensive score is the optimal heat sink required by the module power supply.

[0014] In one embodiment, the weight vector is determined based on expert scores, including:

[0015] Construct a judgment matrix based on expert scores;

[0016] The judgment matrix is ​​normalized to obtain a column-normalized matrix.

[0017] The weight vector is determined by calculating the row average of the column normalized matrix.

[0018] In one embodiment, row averaging is performed on the column-normalized matrix to determine the weight vector, including:

[0019] The initial weight vector is obtained by calculating the row average of the column normalized matrix;

[0020] Calculate the maximum eigenvalue based on the initial weight vector and the judgment matrix;

[0021] Calculate the consistency index based on the largest eigenvalue;

[0022] Determine the consistency ratio based on the consistency index;

[0023] 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] In one embodiment, based on a finite element simulation model and a thermo-structure interaction analysis method, the resulting data on structural influencing factors are determined, including:

[0025] 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.

[0026] Based on material properties, determine the power loss of key heat-generating components in the modular power supply;

[0027] The power loss is input into the steady-state temperature field, and the heat transfer coefficient and temperature environment are set in the steady-state temperature field to obtain the temperature distribution result of the module power supply.

[0028] Input the temperature distribution results into the static structure to determine the structural influencing factors of the module power supply.

[0029] In one embodiment, the entropy weight of each structural influencing factor is determined based on the resulting data of structural influencing factors, including:

[0030] The results of the structural influencing factors were standardized to obtain the corresponding standardized data.

[0031] Based on standardized data, determine the probability distribution of each structural influencing factor;

[0032] Based on the probability distribution of each structural influencing factor, determine the information entropy corresponding to each structural influencing factor;

[0033] Based on the information entropy of each structural influencing factor, determine the entropy weight corresponding to each structural influencing factor.

[0034] In one embodiment, a comprehensive score for heat sinks of different specifications is calculated based on the combined weights of various structural influencing factors, including:

[0035] Based on 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.

[0036] As can be seen from the technical solutions provided in the embodiments of this specification above, this solution utilizes the analytic hierarchy process (AHP) to systematically evaluate the heat sink structure. Based on thermo-structure coupling, through the coupling of the temperature field and the structural field, it can more accurately reflect the temperature rise and deformation of the modular power supply when using heat sinks of different specifications. Using this data as a driving force, it overcomes the limitations of subjective evaluation, integrates multiple indicators, and uses the entropy weight method for quantitative analysis, thus more scientifically scoring different modular power supply heat sink structures. The scheme with the highest score is the optimal design, which improves the reliability of the structure while ensuring the heat sink achieves its heat dissipation purpose. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 A flowchart illustrating the multi-objective evaluation method for modular power supply heat sinks based on hierarchical analysis provided in this application;

[0039] Figure 2 This is a schematic diagram of the hierarchical structure of the structural influencing factors of the module power supply heat sink provided in this application. Detailed Implementation

[0040] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0041] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0042] Various modifications and variations can be made to the specific embodiments described in this application without departing from the scope or spirit of this application, as will be apparent to those skilled in the art. Other embodiments derived from this application will be obvious to those skilled in the art. This application specification and embodiments are merely exemplary.

[0043] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.

[0044] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0045] Reference Figure 1 It illustrates a flowchart of a multi-objective evaluation method for a module power supply heat sink based on hierarchical analysis, applicable to embodiments of this application.

[0046] like Figure 1 As shown, the multi-objective evaluation method for modular power supply heat sinks based on hierarchical analysis can include:

[0047] S110. Determine the structural influencing factors of the module power supply heat sink based on the analytic hierarchy process (AHP). The structural influencing factors include: temperature, deformation, stress, and weight.

[0048] Specifically, establish a radiator design evaluation system, such as Figure 2 As shown, according to AHP, the hierarchical structure of the factors affecting the power supply heatsink structure of this module is as follows:

[0049] Target layer: Factors influencing radiator structure optimization;

[0050] Criterion layer: temperature, structure;

[0051] Factors: temperature, deformation, stress, and weight. Temperature refers to the highest temperature, deformation to the maximum deformation, and stress to the maximum equivalent stress.

[0052] S120. Experts score the structural influencing factors and determine the weight vector based on the expert scores.

[0053] The weight vector, determined based on expert scoring, includes:

[0054] Based on expert scores, a judgment matrix is ​​constructed; where the value of each element in the judgment matrix is: the importance of one factor in the factor layer of the hierarchical structure of factors affecting the module power supply heat sink structure to the importance of another element;

[0055] The judgment matrix is ​​normalized to obtain a column-normalized matrix.

[0056] Calculate the row average of the column-normalized matrix to determine the weight vector, including:

[0057] The initial weight vector is obtained by calculating the row average of the column normalized matrix;

[0058] Calculate the maximum eigenvalue based on the initial weight vector and the judgment matrix;

[0059] Calculate the consistency index based on the largest eigenvalue;

[0060] Determine the consistency ratio based on the consistency index;

[0061] 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.

[0062] Specifically, the experts used a 1-9 scale for scoring, where 1 indicates equal importance, 3 indicates slightly important, 5 indicates significantly important, 7 indicates strongly important, 9 indicates extremely important, and 2, 4, 6, and 8 indicate median values.

[0063] For example, Table 1 below is an expert scoring table.

[0064] Table 1 Expert Scoring Sheet

[0065]

[0066] Based on Table 1 above, the judgment matrix is ​​obtained. for:

[0067]

[0068] by Taking the 1 / 3 in the 2nd row of the 1st column as an example, it means that the importance of deformation to temperature is 1 / 3, and the meanings of other elements are deduced by analogy.

[0069] Divide each column element in the judgment matrix by the sum of that column to obtain the column normalized matrix.

[0070] The initial weight vector is obtained by calculating the row average of the column normalized matrix. The corresponding initial weight vectors are obtained from Table 1 above. for:

[0071] .

[0072] The following is a consistency check to calculate the largest eigenvalue. :

[0073]

[0074] in, To determine the matrix, The initial weight vector, n This represents the total number of elements among the structural influencing factors. n =4, i For example, the element numbering in the structural influencing factors. i =1 indicates temperature. i =2 indicates a transformation. i =3 indicates stress. i =4 indicates weight.

[0075] Based on Table 1 above, the corresponding maximum eigenvalue is obtained. .

[0076] The consistency index is calculated according to the following formula. :

[0077]

[0078] Based on Table 1 above, the consistency index is obtained as follows: .

[0079] The consistency ratio is calculated using the following formula. :

[0080]

[0081] Among them, according to the judgment matrix RI is the random consistency index of a fourth-order matrix, with a value of 0.9.

[0082] The preset threshold can be set according to actual needs; for example, the preset threshold is 0.1.

[0083] Based on Table 1 and RI above, the consistency ratio is obtained. Given that CR≈0.0441<0.1, the initial weight vector obtained above is used as the final weight vector after verification. .

[0084] If the obtained CR≥0.1, adjust the judgment matrix until the obtained consistency ratio is less than the preset threshold, and use the initial weight vector corresponding to this time as the final weight vector.

[0085] S130. Establish a finite element simulation model of the modular power supply, including the heat sink.

[0086] Specifically, a finite element simulation model of the power supply module, including the heatsink, is created using modeling software such as SOLIDWORKS. This finite element simulation model includes all critical components, such as the aluminum alloy casing, PCB board, heatsink, key heat-generating elements, pins, bolts, and other fasteners. The bottom of the power supply module is fixedly supported to simulate welding and fixing conditions. Understandably, minor features that do not affect thermal analysis, such as chamfers and small holes, can be removed from the finite element simulation model. The finite element simulation model can include both a heatsink model and a power supply module model. Understandably, when evaluating the performance of different heatsink specifications applied to the power supply module, only the heatsink model in the finite element simulation model needs to be replaced.

[0087] It's understandable, as the weight data among the structural influencing factors can be read from the finite element simulation model.

[0088] S140. Based on the finite element simulation model and the thermo-structure coupling analysis method, the results data for determining the structural influencing factors include:

[0089] 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.

[0090] Based on material properties, determine the power loss of key heat-generating components in the modular power supply;

[0091] The power loss is input into the steady-state temperature field, and the heat transfer coefficient and temperature environment are set in the steady-state temperature field to obtain the temperature distribution result of the module power supply.

[0092] Input the temperature distribution results into the static structure to determine the structural influencing factors of the module power supply.

[0093] Specifically, the analysis method for thermo-structure coupling includes setting the material properties of each component of the modular power supply and analyzing the steady-state temperature field and static structure.

[0094] The simulation platform can be ANSYS WORKBENCH. The finite element simulation model is imported into ANSYS WORKBENCH, and then the material properties of each component in the model are set according to actual conditions to ensure the completeness and accuracy of the thermal and structural parameters of various materials. For example, for aluminum alloy casings, heat sinks, and PCB boards, input mechanical and thermal parameters such as thermal conductivity, specific heat capacity, density, and coefficient of thermal expansion. These parameters can be obtained from manufacturer datasheets or measured values ​​to ensure simulation reliability.

[0095] The finite element simulation model is meshed to obtain the mesh model of the modular power supply, which determines the accuracy of the spatial distribution of heat sources in the finite element simulation model. Understandably, when meshing, it is necessary to select appropriate mesh type and density.

[0096] The power loss of key heat-generating components used in the power supply of the computing module is analyzed, exemplified by common heat-generating components such as MOSFETs and planar transformers. and The calculation formulas are as follows:

[0097]

[0098]

[0099] in, This refers to the power consumption of the MOSFET when the module power supply is operating. The on-resistance between the drain and source when the circuit is in the on-state. This is the load current; This refers to the power consumption of the planar transformer during module operation. For winding losses, This refers to core loss.

[0100] 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 MOSFET power loss. =0.02W, power loss of the planar transformer =5.47W.

[0101] The calculated power loss of the key heating element is used as the input to the steady-state temperature field. Temperature field analysis is performed on the module power supply, and steady-state temperature field simulation calculation is performed using ANSYS Steady-State Thermal.

[0102] In a steady-state temperature field, the heat transfer coefficient and ambient temperature are set, the module power supply is located under natural air convection conditions, and the temperature distribution results are read.

[0103] The heat sink design method is applied to the power supply module with heat dissipation requirements, taking into account both normal temperature and high temperature operating conditions. Therefore, the simulated power supply module operating conditions include: high temperature operating environment, generally 85℃; and normal temperature operating environment, generally 25℃.

[0104] The temperature distribution structure obtained above is used as the input of the static structure. Static structure analysis is performed using ANSYS StaticStructural, the boundary conditions of the module power supply are set, and the deformation and stress distribution results are read.

[0105] S150. Based on the results data of structural influencing factors, determine the entropy weight of each structural influencing factor, including:

[0106] The results of the structural influencing factors were standardized to obtain the corresponding standardized data.

[0107] Based on standardized data, determine the probability distribution of each structural influencing factor;

[0108] Based on the probability distribution of each structural influencing factor, determine the information entropy corresponding to each structural influencing factor;

[0109] Based on the information entropy of each structural influencing factor, determine the entropy weight corresponding to each structural influencing factor.

[0110] Specifically, the range method is used to standardize the data. Temperature, deformation, stress, and weight are all negative indicators. The standardization formula is as follows:

[0111]

[0112] in, To standardize data, For data to be standardized, i This refers to the element number among the structural influencing factors. j Structural influencing factors for different specifications of heat sinks; for example This indicates the temperature data in the radiator of specification one; Elements among structural influencing factors i The maximum value in the corresponding sequence, Elements among structural influencing factors i The minimum value in the corresponding sequence, where the sequence is formed from the results of structural influencing factors corresponding to different specifications of heat sinks. For example, This represents the maximum value among the simulation results of the highest temperature on the surface of the module power supply when using heat sinks of different specifications.

[0113] Probability distribution of each structural influencing factor The calculation formula is:

[0114]

[0115] in, a This refers to the specifications and quantity of the heatsink. For example, This refers to the probability distribution of temperature.

[0116] Information entropy of each structural influencing factor The calculation formula is:

[0117]

[0118] For example, The information entropy refers to temperature.

[0119] Entropy weighting of each structural influencing factor based on the entropy weighting method The calculation formula is:

[0120]

[0121] For example, based on Table 1 above, the highest 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%.

[0122] 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:

[0123]

[0124] in, Subjective weighting percentage For objective weighting percentages, and The value can be set according to actual needs, for example, The value is 0.3. The value is 0.7.

[0125] For example, based on Table 1 above, we get:

[0126] =

[0127] =

[0128] =

[0129] =

[0130] S170. Based on the comprehensive weight of each structural influencing factor, calculate the comprehensive score of heat sinks of different specifications. The heat sink with the highest comprehensive score is the optimal heat sink required by the module power supply.

[0131] The comprehensive score for radiators of different specifications is calculated based on the combined weight of each structural influencing factor. This includes: calculating the comprehensive score for radiators of different specifications based on the combined weight of each structural influencing factor and the standardized data of each structural influencing factor.

[0132]

[0133] Table 2 shows the comprehensive scores for different specifications of radiators from Scheme A to Scheme I. For example, Scheme A uses a specification 1 radiator, Scheme I uses a specification 9 radiator, and so on. Among them, Scheme A uses a radiator with 3 teeth, Scheme B uses a radiator with 6 teeth, and so on.

[0134] Table 2. Overall rating of radiators of different specifications

[0135]

[0136] In this embodiment, the heat sink corresponding to scheme F is the optimal heat sink required by the module power supply.

[0137] The multi-objective evaluation method for modular power supply heat sinks based on hierarchical analysis provided in this application systematically evaluates the heat sink structure using the hierarchical analysis method. Based on thermo-structure coupling, it can more accurately reflect the temperature rise and deformation of the modular power supply when using heat sinks of different specifications through the coupling of temperature field and structural field. Using this data as a driving force, it overcomes the limitations of subjective evaluation, integrates multiple indicators, and uses the entropy weight method for quantitative analysis to more scientifically score different modular power supply heat sink structures. The scheme with the highest score is the optimal design, which improves the reliability of the structure while ensuring the heat sink achieves the heat dissipation purpose.

[0138] It should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0139] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

Claims

1. A multi-objective evaluation method for modular power supply heat sinks based on hierarchical analysis, characterized in that, The method includes: The structural influencing factors of the module power supply heat sink were determined using the analytic hierarchy process (AHP). These factors included temperature, deformation, stress, and weight. The structural influencing factors are scored by experts, and a weight vector is determined based on the expert scores; Establish a finite element simulation model of the modular power supply, including the heat sink; Based on the finite element simulation model and the thermo-structure 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. Based on the material properties, determine the power loss of the key heat-generating components in the module power supply; The power loss is input into the steady-state temperature field, and the heat transfer coefficient and temperature environment are set in the steady-state temperature field to obtain the temperature distribution result of the module power supply. The temperature distribution results are input into the static structure to determine the structural influencing factors of the module power supply. Based on the results data of the structural influencing factors, determine the entropy weight of each structural influencing factor; Based on the weight vector and the entropy weight of each of the structural influencing factors, the comprehensive weight corresponding to each of the structural influencing factors is determined. : in, Subjective weighting percentage For objective weighting percentages, For the weight vector, The entropy weights of each structural influencing factor, i The element number is one of the structural influencing factors. Based on the comprehensive weight of each structural influencing factor, a comprehensive score is calculated for heat sinks of different specifications. The heat sink with 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, The determination of the weight vector based on the expert scores includes: Construct a judgment matrix based on the expert scores; The judgment matrix is ​​subjected to column normalization to obtain a column normalized matrix; The weight vector is determined by calculating the row average of the column normalized matrix.

3. The method according to claim 2, characterized in that, The step of calculating the row average of the column normalized matrix to determine the weight vector includes: The initial weight vector is obtained by calculating the row average of the column normalized matrix. Calculate the maximum eigenvalue based on the initial weight vector and the judgment matrix; Calculate the consistency index based on the maximum eigenvalue; Determine the consistency ratio based on the aforementioned 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, and the initial weight vector corresponding to this time is used as the weight vector.

4. The method according to claim 1, characterized in that, The step of determining the entropy weight of each structural influencing factor based on the result data of the structural influencing factors includes: The results of the structural influencing factors were standardized to obtain the corresponding standardized data. Based on the standardized data, determine the probability distribution of each of the structural influencing factors; Based on the probability distribution of each of the structural influencing factors, determine the information entropy corresponding to each of the structural influencing factors; Based on the information entropy of each of the structural influencing factors, determine the entropy weight corresponding to each of the structural influencing factors.

5. The method according to claim 4, characterized in that, The calculation of the comprehensive score for heat sinks of different specifications based on the comprehensive weight of each structural influencing factor includes: Based on 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.

Images