Interface heat conductivity coefficient distribution optimization design method and system for improving contact thermal performance of assembly interface

Abstract

The invention discloses an interface heat conductivity coefficient distribution optimization design method and system for improving the contact thermal performance of an assembly interface, and the method comprises the steps: obtaining the contact heat dissipation surface microstructure features of a part of an electronic chip packaging system, and constructing a contact thermal performance numerical analysis model; performing multiple iterations on the heat conductivity coefficient distribution of the design area by adopting a contact thermal performance numerical analysis model to obtain the heat conductivity coefficient distribution and contact thermal resistance; judging whether each iteration meets an iteration convergence criterion or not according to the heat conductivity coefficient distribution and the contact thermal resistance; and if the iterative convergence criterion is met, outputting heat conductivity coefficient distribution and contact thermal resistance. The temperature transfer path of the assembly interface is controlled by designing the surface heat conductivity coefficient distribution of the assembly interface, and temperature gradient distribution homogenization is truly achieved by applying the innovative design thought of'heterogeneous' heat conductivity coefficient distribution.

Description

Technical Field

[0001] The present invention belongs to the technical field of mechanical design, and specifically relates to an interface thermal conductivity distribution optimization design method and system for improving the contact thermal performance of an assembly interface. Background Art

[0002] The development trend of miniaturization, integration and high assembly density of electronic equipment has led to the problem of large-scale heat accumulation, resulting in insufficient system heat dissipation performance, which seriously affects the working performance and performance stability of electronic equipment throughout its service life. The journal Nature pointed out that due to the inability to solve the heat dissipation problem, "Moore's Law" is about to fail. How to effectively ensure the heat dissipation performance of electronic equipment has become a hot issue that needs to be solved urgently. Electronic equipment is an assembly with specific functions assembled by parts in a certain connection method. The internal loads and physical properties are transmitted between the structures through the assembly interface. The assembly interface destroys the continuity of temperature and stress transmission between electronic equipment parts, and its contact thermal resistance (TCR) accounts for a very high proportion of the overall thermal resistance, far exceeding the influence of body thermal resistance. The TCR caused by the non-ideal real contact state of the assembly interface is the main reason for the insufficient contact thermal performance and overall performance of electronic equipment. As a multidisciplinary problem involving mechanics, heat transfer, materials and other related fields, TCR has important research value and practical application value. Reducing TCR can effectively improve the heat transfer efficiency, prevent equipment overheating, damage, performance degradation, and problems caused by local thermal stress and hot spots, thereby improving the reliability and service life of the equipment. Therefore, finding new and efficient technologies to improve contact heat transfer performance has become a prominent issue in addressing the thermal management challenges of heat-sensitive devices in various fields.

[0003] The existing macro-control and surface treatment technologies for enhancing contact thermal performance are insufficient in terms of control performance. Thermal interface materials are difficult to prepare and their thickness cannot adapt to the trend of integrated development. As a result, the existing technology has already faced a technical ceiling in terms of enhancing contact thermal performance. Then, starting from the nature of the formation of contact thermal resistance, its physical essence is that the rough and uneven contact interface leads to insufficient and uneven contact at the contact interface, resulting in insufficient contact thermal performance. From the perspective of energy dissipation, this is because the heat transfer energy dissipation of the assembly interface has not been minimized. Summary of the invention

[0004] The present invention aims to solve the bottleneck of improving contact thermal performance caused by the existing "homogenization" design thinking, and aims to provide an interface thermal conductivity distribution optimization design method and system for improving the contact thermal performance of the assembly interface. By actively designing the thermal conductivity distribution of the assembly interface, the purpose of reducing the contact thermal resistance of the assembly interface is achieved, and the service life and stability of highly heat-sensitive mechanical equipment such as electronic chip packaging systems are effectively guaranteed.

[0005] In order to achieve the purpose of the present invention, the technical solution adopted is:

[0006] A method for optimizing the distribution of thermal conductivity of an interface for improving the contact thermal performance of an assembly interface comprises the following steps:

[0007] Obtaining the contact and heat dissipation surface micro-morphology characteristics of the components of the electronic chip packaging system;

[0008] According to the microscopic morphology characteristics of the contact heat dissipation surface of the component, a numerical analysis model of contact heat performance is constructed;

[0009] The contact thermal performance numerical analysis model is used to iterate the thermal conductivity distribution of the design area multiple times to obtain the thermal conductivity distribution and contact thermal resistance;

[0010] Whether each iteration meets the iterative convergence criterion is determined according to the thermal conductivity distribution and the contact thermal resistance; if the iterative convergence criterion is met, the thermal conductivity distribution and the contact thermal resistance are output; if the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of using the contact thermal performance numerical analysis model to iterate the thermal conductivity distribution of the design area for multiple times is returned.

[0011] Furthermore, a laser confocal roughness testing system is used to obtain the microscopic morphology characteristics of the contact heat dissipation surface of key components.

[0012] Furthermore, the rough surface is reconstructed by mapping to the contact surface mesh unit nodes with the same sampling rate, and then a numerical analysis model of contact thermal performance considering the real microscopic rough surface is constructed.

[0013] Furthermore, the iterative design criterion for thermal conductivity distribution is the temperature gradient uniform distribution principle extended from the minimum extreme value principle of energy dissipation in the heat transfer process, which is expressed as follows:

[0014]

[0015] Among them, k n)1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design domain mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t Temperature gradient, λ—regulation factor, k min — Minimum thermal conductivity limit for the design area, k max —Maximum limit of thermal conductivity in the design area.

[0016] Furthermore, the goal of the iterative design criterion for thermal conductivity distribution is to achieve temperature gradient homogenization and minimize contact thermal resistance by optimizing the thermal conductivity distribution.

[0017] Furthermore, the design region is an assembly region with a set thickness in a direction perpendicular to the contact surface, and the design sub-region is each grid unit in the design region.

[0018] Furthermore, the contact thermal resistance TCR is calculated by the following formula:

[0019]

[0020] Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —Average heat flux on the lower contact surface of the assembly.

[0021] Furthermore, the iterative convergence criteria include the convergence of the maximum number of iterations, the convergence of the design target optimization rate, and the convergence of the rate of change of two adjacent design targets.

[0022] Furthermore, the iterative convergence criterion is:

[0023]

[0024] Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for the n-1th, nth, and n+1th iterations, TCR(k) 0 —Initial TCR results before optimization, —convergence threshold of optimization target reduction rate, ξ—convergence threshold of adjacent optimization target change rate.

[0025] An interface thermal conductivity distribution optimization design system for improving the contact thermal performance of an assembly interface, comprising:

[0026] A microscopic morphology feature acquisition module is used to acquire the microscopic morphology features of the contact and heat dissipation surface of the component;

[0027] The contact thermal performance numerical analysis model building module is used to build a contact thermal performance numerical analysis model based on the microscopic morphology characteristics of the contact heat dissipation surface of the component;

[0028] Thermal conductivity distribution and contact thermal resistance calculation module, used to perform multiple iterative calculations on the thermal conductivity distribution of the design area using the contact thermal performance numerical analysis model to obtain the thermal conductivity distribution and contact thermal resistance;

[0029] The judgment module is used to judge whether each iteration meets the iteration convergence criterion according to the thermal conductivity distribution and the contact thermal resistance; if the iteration convergence criterion is met, the thermal conductivity distribution and the contact thermal resistance are output; if the iteration convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of multiple iterations of the thermal conductivity distribution of the design area using the contact thermal performance numerical analysis model is returned.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention analyzes the physical nature of the formation of contact thermal resistance from the perspective of the energy dissipation mechanism in the heat transfer process for the first time. Aiming at the technical ceiling of enhanced contact thermal performance caused by the insufficient control performance of existing macro-control and surface treatment technologies for enhanced contact thermal performance, as well as the difficulty in preparing thermal interface materials and the inability of their own thickness to adapt to the development trend of integration, the present invention creatively proposes to control the temperature transfer path of the assembly interface by designing the surface thermal conductivity distribution of the assembly interface, and to truly achieve uniform temperature gradient distribution by applying the innovative design thinking of "heterogeneous" thermal conductivity distribution, thus overcoming the problem of uneven temperature gradient distribution caused by the traditional "homogeneous" thermal conductivity distribution of the assembly interface, and further achieving effective reduction of contact thermal resistance by ensuring the minimization of energy dissipation. The present invention can break through the bottleneck of improving contact thermal performance caused by the traditional "homogeneous" design thinking, and fundamentally solve the problem of insufficient contact thermal performance caused by contact thermal resistance in the heat transfer process based on the physical nature of heat transfer, significantly improving the contact thermal performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems, thereby effectively ensuring their service life and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flow chart of the interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface of the present invention;

[0033] Figure 2 It is a schematic diagram of the numerical analysis model;

[0034] Figure 3 Temperature distribution cloud diagram of the master and slave assembly interfaces before optimization design; (a) is the master assembly interface, (b) is the slave assembly interface;

[0035] Figure 4 Temperature distribution cloud diagram of the master and slave assembly interfaces after optimization design; (a) is the master assembly interface, (b) is the slave assembly interface;

[0036] Figure 5 A schematic diagram of the structure of the interface thermal conductivity distribution optimization design system for improving the contact thermal performance of the assembly interface of the present invention. DETAILED DESCRIPTION

[0037] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. The preferred embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thoroughly and comprehensively understood.

[0038] Starting from the perspective of minimizing energy dissipation, the thermal conductivity distribution of the assembly interface is actively designed to achieve uniform temperature gradient distribution and thus meet the minimum energy dissipation, and to achieve a fast and accurate layout of the thermal conductivity of the assembly interface that matches the optimal contact thermal performance. The present invention can break through the bottleneck of improving contact thermal performance caused by traditional "homogenization" design thinking, and significantly improve the contact thermal performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems, thereby effectively ensuring their service life and stability.

[0039] The present invention adopts the innovative design concept of "heterogeneous" thermal conductivity distribution, improves the contact heat performance by actively designing the thermal conductivity distribution of the assembly interface, and effectively ensures the service performance and stability of highly heat-sensitive mechanical equipment such as electronic chip packaging systems.

[0040] See also Figure 1 The present invention proposes an interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface, comprising the following steps:

[0041] 1) Constructing a numerical analysis model for contact thermal performance: The main reason for the insufficient heat dissipation performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems is the contact thermal resistance caused by the microscopic roughness of the assembly interface surface. Reconstructing the real contact surface micromorphology is the premise and necessary condition for constructing a numerical analysis model for contact thermal resistance. Therefore, the laser confocal roughness test system is first used to obtain the microscopic morphology characteristics of the contact heat dissipation surface of key components, and the rough surface is reconstructed by mapping to the contact surface grid unit nodes with the same sampling rate, and then a numerical analysis model for contact thermal performance considering the real microscopic rough surface is constructed.

[0042] It should be noted that in order to ensure that the reconstructed rough contact surface can meet the coordinated requirements of computational accuracy and computational time, it is necessary to carry out mesh independence analysis of the numerical analysis model that depends on the rough surface sampling rate, and then find the minimum micro-morphology sampling rate requirement that meets the computational accuracy requirements. The constructed contact thermal performance numerical analysis model is a mechanical-heat transfer double iterative sequential coupling analysis that considers secondary thermal effects such as thermal stress and thermal softening. The final contact state in the mechanical analysis is used as the initial state of the heat transfer analysis to realize the transfer of mechanical analysis results to heat transfer analysis. The method of defining a predefined temperature field is used to initialize the mechanical analysis of the entire process of temperature distribution in the heat transfer analysis to realize the transfer of heat transfer analysis results to mechanical analysis, thereby achieving high-accuracy analysis of contact thermal performance, which can be used for contact thermal performance analysis under various working conditions.

[0043] 2) Define the design area and design sub-area: The optimization design method of the present invention is to find the thermal conductivity distribution of the assembly interface that satisfies the minimum contact thermal resistance under the thermal conductivity integral restriction. The physical equation can be expressed as:

[0044]

[0045] Among them, k is the thermal conductivity distribution of the design area, e1 is the grid unit of the design sub-area, k(e1) is the thermal conductivity of the grid unit of the design sub-area, k0 is the initial thermal conductivity value, and V is the volume size of the design area. In addition, in order to find the optimal thermal conductivity distribution, the original total integral limit of the thermal conductivity of the design area can be changed to unlimited to find the thermal conductivity distribution that meets the best contact thermal performance.

[0046] Therefore, it is first necessary to define the assembly area with a certain thickness perpendicular to the contact surface as the design area, each grid unit in the design area as a design sub-area, the thermal conductivity of each design sub-area as the design sub-variable, and the thermal conductivity distribution in the entire design area as the entire design variable.

[0047] Among them, the thickness of the design area is determined according to the actual manufacturing process and the size of the assembly. Different design area thicknesses have a greater impact on the optimization design results. In theory, increasing the thickness of the design area can improve the optimization design effect. Therefore, it is necessary to determine the optimal design area thickness according to actual needs. In order to ensure the precise regulation of the thermal conductivity distribution, each grid unit in the design area is the smallest design sub-area. Of course, in order to match the actual manufacturing process size limitations, the number of grid units contained in each sub-design area can be defined according to actual needs. The optimal thermal conductivity distribution and the contact thermal performance results after optimization corresponding to the sizes of different sub-design areas are different.

[0048] 3) Define the thermal conductivity distribution of the design area: Define the unit thermal conductivity of each design sub-area, initialize the thermal conductivity distribution to a uniform and consistent thermal conductivity value in traditional design thinking, obtain the defined thermal conductivity distribution of the design area, and use this analysis as a reference result before optimizing the design. Subsequently, in order to find the optimal thermal conductivity distribution, redefine the material thermal conductivity distribution of the design area in the numerical analysis model according to the thermal conductivity distribution updated in each iteration step.

[0049] 4) Calculate the temperature gradient distribution and contact thermal performance of the design area: Based on the thermal conductivity distribution of the design area defined in step 3), the contact thermal performance numerical analysis model is used to calculate the temperature gradient distribution of the design area for iterative updating of design variables, and solve the design target, i.e., the contact thermal resistance result, under the thermal conductivity distribution of the design area defined in step 3) for iterative convergence judgment. Among them, the design target, i.e., the contact thermal resistance TCR, is defined as:

[0050]

[0051] Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —Average heat flux on the contact surface under the assembly. Therefore, based on the contact surface temperature and heat flux distribution results obtained by the numerical analysis of contact thermal performance, the contact thermal resistance results under the thermal conductivity distribution state in different design areas are calculated.

[0052] 5) Determine whether the convergence condition is met: The iterative design criterion for thermal conductivity distribution is the temperature gradient uniform distribution principle extended from the minimum extreme value principle of energy dissipation in the heat transfer process. The detailed formula is as follows:

[0053]

[0054] Among them, k n+1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design domain mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t The temperature gradient, λ is the control factor, which is used to determine whether the thermal conductivity distribution meets the total integral limit requirement. If it is equal to 1, the total integral of the thermal conductivity distribution in the design area is limited. If it is greater than 1, the optimal thermal conductivity distribution is found under the condition of no thermal conductivity restriction. k min — Minimum thermal conductivity limit for the design area, kmax —Maximum limit of thermal conductivity in the design area.

[0055] The specific steps of updating the thermal conductivity are to apply the iterative design criteria and update the thermal conductivity distribution of the next iteration step based on the temperature gradient distribution and thermal conductivity distribution obtained in the previous iteration step. The ultimate goal is to achieve temperature gradient homogenization by optimizing the thermal conductivity distribution and thus minimize the contact thermal resistance.

[0056] The thermal conductivity distribution k of the design area is iterated multiple times using the iterative design criterion of thermal conductivity distribution to obtain the design target result. Whether each iteration meets the iterative convergence criterion is determined according to the design target result. If the iterative convergence criterion is met, proceed to the next step 6). If the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated based on the iterative design criterion, and the thermal conductivity distribution of the design area in the numerical analysis model is updated, and then proceed to step 4).

[0057] There are three iterative convergence criteria, namely, the maximum number of iterations convergence, the design target optimization rate convergence, and the convergence of the rate of change of two adjacent design targets, which can be specifically expressed as:

[0058]

[0059] Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for the n-1th, nth, and n+1th iterations, TCR(k) 0 —Initial TCR results before optimization, —convergence threshold of optimization target reduction rate, ξ—convergence threshold of adjacent optimization target change rate.

[0060] 6) Output the optimized thermal conductivity distribution and contact thermal resistance calculation results that meet the iterative convergence criteria. The output optimized thermal conductivity distribution is set according to the actual optimization design. The thermal conductivity distribution in the vertical direction of the assembly interface is uniformed or differentiated. The differentiated distribution can obtain better contact thermal performance but also brings processing difficulties.

[0061] Example 1

[0062] The present invention is described by taking a concrete key assembly interface in an electronic chip packaging system as an example.

[0063] The overall analysis process of this embodiment is as follows Figure 1 As shown, it mainly includes 6 steps, and the key assembly interface is selected as the research object. The specific steps are as follows:

[0064] 1) The key assembly interface in the electronic chip packaging system is selected as the specific research object, and the laser confocal roughness test system is used to obtain the microscopic morphology characteristics of the contact surface. The rough surface is reconstructed by mapping it to the contact surface grid unit nodes with the same sampling rate, and then a contact thermal performance numerical analysis model considering the real microscopic rough surface is constructed. In addition, this numerical analysis model is the optimal numerical model considering the surface microscopic morphology sampling rate and grid size independence analysis. Figure 2 As shown in the figure, a uniform pressure load of 3 MPa is applied to the upper surface, and the load condition for heat transfer analysis is the different temperature heat sources on the left and right sides of the upper surface, which are T r =573K and T l =373K. First, the contact mechanical analysis is applied to obtain the initial contact state, and then the initial contact state is used as the initial mesh state of the contact heat transfer analysis to carry out the contact heat transfer analysis. Subsequently, the obtained temperature history is used in the form of a predefined temperature field to carry out a secondary contact state analysis that considers the effects of thermal stress, thermal softening, etc. Finally, the secondary contact state is used as the initial mesh state of the contact heat transfer analysis to carry out the contact heat transfer analysis to obtain the final temperature and heat flux distribution state.

[0065] 2) The optimization design method is to find the thermal conductivity distribution of the assembly interface that satisfies the minimum contact thermal resistance under the thermal conductivity integral constraint. Its physical equation can be expressed as:

[0066]

[0067] Among them, k is the thermal conductivity distribution of the design area, e1 is the grid unit of the design sub-area, k(e1) is the thermal conductivity of the grid unit of the design sub-area, k0 is the initial thermal conductivity value, and V is the volume size of the design area. In addition, in order to find the optimal thermal conductivity distribution, the original total integral limit of the thermal conductivity of the design area can be changed to unlimited to find the thermal conductivity distribution that meets the best contact thermal performance.

[0068] Therefore, according to the machining accuracy and size limitation of the surface coating manufacturing process, the assembly area with a thickness of 0.3 mm in the vertical direction from the contact surface is defined as the design area. Each grid unit in the design area is a design sub-area. The thermal conductivity of each design sub-area is the design sub-variable, and the thermal conductivity distribution in the entire design area is the entire design variable. The detailed size and design area division of the numerical analysis model are as follows: Figure 2 shown.

[0069] 3) Use a cyclic algorithm to define the unit thermal conductivity of each design sub-area, initialize the thermal conductivity distribution to a uniform and consistent thermal conductivity value in traditional design thinking, and use this analysis as a reference result before optimizing the design. The thermal conductivity value initialized for this design object is HTA material, and the thermal conductivity of HTA material is defined as 11W / mk. Subsequently, in order to find the optimal thermal conductivity distribution, the material thermal conductivity distribution of the design area in the numerical analysis model is redefined according to the thermal conductivity distribution updated in each iteration step.

[0070] 4) Based on the defined design area thermal conductivity distribution, the contact thermal performance numerical analysis model is used to calculate the design area temperature gradient distribution for the design variable update iteration, and the design target under the thermal conductivity distribution condition, i.e., the contact thermal resistance result, is solved for iterative convergence judgment. Among them, the design target, i.e., the contact thermal resistance TCR, is defined as

[0071]

[0072] Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —Average heat flux on the contact surface under the assembly. Therefore, based on the contact surface temperature and heat flux distribution results obtained by the numerical analysis of contact thermal performance, the contact thermal resistance results under the thermal conductivity distribution state in different design areas are calculated.

[0073] 5) Iterative design criteria for thermal conductivity distribution The principle of uniform distribution of temperature gradient is extended from the principle of minimum extreme value of energy dissipation in heat transfer process. The detailed formula is expressed as:

[0074]

[0075]

[0076] Among them, k n+1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design domain mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t The temperature gradient, λ is the control factor, which is used to determine whether the thermal conductivity distribution meets the total integral limit requirement. If it is equal to 1, the total integral of the thermal conductivity distribution in the design area is limited. If it is greater than 1, the optimal thermal conductivity distribution is found under the condition of no thermal conductivity restriction. k min— Minimum thermal conductivity limit for the design area, k max —Maximum value limit of thermal conductivity in the design area.

[0077] The specific steps of updating the thermal conductivity are to apply the iterative design criteria and update the thermal conductivity distribution of the next iteration step based on the temperature gradient distribution and thermal conductivity distribution obtained in the previous iteration step. The ultimate goal is to achieve temperature gradient homogenization by optimizing the thermal conductivity distribution and thus minimize the contact thermal resistance.

[0078] Determine whether this iteration meets the iteration convergence criteria based on the design target results. If so, proceed to the next step 6). If not, calculate the thermal conductivity distribution of the next iteration based on the iterative design criteria, update the thermal conductivity distribution of the design area in the numerical analysis model, and proceed to step 4).

[0079] There are three iterative convergence criteria, namely, the maximum number of iterations convergence, the design target optimization rate convergence, and the convergence of the rate of change of two adjacent design targets, which can be specifically expressed as:

[0080]

[0081] Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for the n-1th, nth, and n+1th iterations, TCR(k) 0 —Initial TCR results before optimization, —Optimization target reduction rate convergence threshold, ξ—adjacent optimization target change rate convergence threshold. The specific iterative convergence criterion of this design object is the convergence of two adjacent design target change rates, that is, the adjacent optimization target change rate convergence threshold ξ=0.0005.

[0082] 6) Output the optimized thermal conductivity distribution and contact thermal resistance calculation results that meet the iterative convergence criteria. In order to improve the calculation efficiency, the design variables are evenly distributed in the vertical direction of the design area in this optimization design, so only the thermal conductivity distribution of the contact surface mesh unit needs to be output.

[0083] The beneficial effects of the present invention are further illustrated by taking the key assembly interface in the electronic chip packaging system as an example. The temperature distribution cloud diagram of the master and slave assembly interfaces before the "heterogeneous" thermal conductivity distribution design is as follows: Figure 3 As shown in (a) and (b), the temperature distribution cloud diagram of the master and slave assembly interfaces after the “heterogeneous” thermal conductivity distribution design is as follows Figure 4 As shown in (a) and (b). Figure 3Due to the introduction of non-uniform temperature distribution on the upper surface and the existence of microscopic surface roughness, the temperature gradient distribution on the contact surface during the heat transfer process is extremely uneven, resulting in a small true contact thermal conductivity, uneven temperature distribution on the upper and lower contact surfaces, and a very high difference in the mean of the temperature distribution. Starting from the energy dissipation and uniformity of the temperature gradient distribution, the temperature gradient distribution is uniformized and the true thermal conductivity is greatly improved by actively designing the thermal conductivity distribution of the assembly interface. Figure 3 and Figure 4 It can be clearly seen that the uniformity of temperature distribution has been greatly improved, the difference in temperature distribution between the upper and lower contact surfaces has been significantly reduced, and the average heat flux has increased. Calculations have found that the contact thermal resistance TCR has been reduced by more than 40%, effectively improving the contact thermal performance.

[0084] Example 2

[0085] See also Figure 5 , an interface thermal conductivity distribution optimization design system for improving the contact thermal performance of the assembly interface, comprising:

[0086] A microscopic morphology feature acquisition module is used to acquire the microscopic morphology features of the contact and heat dissipation surface of the component;

[0087] The contact thermal performance numerical analysis model building module is used to build a contact thermal performance numerical analysis model based on the microscopic morphology characteristics of the contact heat dissipation surface of the component;

[0088] Thermal conductivity distribution and contact thermal resistance calculation module, used to perform multiple iterative calculations on the thermal conductivity distribution of the design area using the contact thermal performance numerical analysis model to obtain the thermal conductivity distribution and contact thermal resistance;

[0089] The judgment module is used to judge whether each iteration meets the iteration convergence criterion according to the thermal conductivity distribution and the contact thermal resistance; if the iteration convergence criterion is met, the thermal conductivity distribution and the contact thermal resistance are output; if the iteration convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of multiple iterations of the thermal conductivity distribution of the design area using the contact thermal performance numerical analysis model is returned.

[0090] The present invention abandons the traditional "homogeneous" design thinking of thermal conductivity of the assembly interface, and innovatively proposes the "heterogeneous" design concept of heat transfer characteristics such as thermal conductivity of the assembly interface for precise control of contact thermal performance. This method takes the numerical analysis model of contact thermal performance of the assembly interface that takes into account the microscopic roughness morphology of the surface as the design object, minimizes the contact thermal resistance of the assembly interface as the design goal, and uses the contact interface area of ​​the assembly and the grid units in the area as the design area and design sub-area, and the thermal conductivity of the grid units in the design area as the design variable; the laser confocal roughness test system is used to obtain the microscopic morphology characteristics of the contact surface, and a numerical analysis model of contact thermal performance that takes into account the real microscopic rough surface and secondary thermal effects is established, thereby achieving accurate prediction of contact thermal characteristics. The numerical analysis model of the contact thermal performance of the assembly interface considering the microscopic roughness of the surface is taken as the design object, the minimization of the contact thermal resistance of the assembly interface is taken as the design goal, the contact interface area of ​​the assembly and the grid units in the area are taken as the design area and the design sub-area, and the thermal conductivity of the grid units in the design area is taken as the design variable; the iterative design criteria of the thermal conductivity distribution of the assembly interface driven by the maximum energy dissipation principle are applied to form a fast and precise control optimization design method for the thermal conductivity distribution of the assembly interface driven by the contact thermal performance, which solves the high computational complexity and weak iterative convergence of the traditional group algorithm, and realizes the fast and precise layout of the thermal conductivity of the assembly interface matching the optimal contact thermal performance. The present invention can break through the bottleneck of improving the contact thermal performance caused by the traditional "homogenization" design thinking, significantly improve the contact thermal performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems, and solve the problems of excessive operating temperature and premature equipment failure caused by local thermal stress caused by insufficient contact thermal performance of highly heat-sensitive mechanical equipment, thereby effectively ensuring its service life and stability.

[0091] The above description is only for the best embodiment of the present invention, but it should not be understood as limiting the claims. The present invention is not limited to the above embodiments, and its specific structure is allowed to be changed. However, all changes made within the protection scope of the independent claims of the present invention are within the protection scope of the present invention.

[0092] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

Claims

1. A method for optimizing the distribution of thermal conductivity of an interface for improving the contact thermal performance of an assembly interface, characterized in that: The following steps are involved: Obtaining the contact and heat dissipation surface micro-morphology characteristics of the components of the electronic chip packaging system; According to the microscopic morphology characteristics of the contact heat dissipation surface of the component, a numerical analysis model of contact heat performance is constructed; The contact thermal performance numerical analysis model is used to iterate the thermal conductivity distribution of the design area multiple times to obtain the thermal conductivity distribution and contact thermal resistance; Determine whether each iteration meets the iteration convergence criterion based on the thermal conductivity distribution and contact thermal resistance; If the iteration convergence criteria are met, the thermal conductivity distribution and contact thermal resistance are output; If the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of using the contact thermal performance numerical analysis model to iterate the thermal conductivity distribution of the design area multiple times is returned.

2. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1 is characterized in that: The laser confocal roughness testing system is used to obtain the microscopic morphology characteristics of the contact heat dissipation surface of key components.

3. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The rough surface is reconstructed by mapping to the contact surface mesh unit nodes with the same sampling rate, and then a numerical analysis model of contact thermal performance considering the real microscopic rough surface is constructed.

4. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The iterative design criterion for thermal conductivity distribution is the temperature gradient uniform distribution principle extended from the minimum extreme value principle of energy dissipation in the heat transfer process, which can be expressed as follows: Among them, k n)1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design domain mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t Temperature gradient, λ—regulation factor, k min — Minimum thermal conductivity limit for the design area, k max —Maximum value limit of thermal conductivity in the design area.

5. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The goal of the iterative design criterion for thermal conductivity distribution is to achieve uniform temperature gradient and minimize contact thermal resistance by optimizing the thermal conductivity distribution.

6. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The design region is the assembly region with a set thickness perpendicular to the contact surface, and the design sub-region is each grid unit in the design region.

7. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The contact thermal resistance TCR is calculated by the following formula: Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —Average heat flux on the lower contact surface of the assembly.

8. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: Iterative convergence criteria include the convergence of the maximum number of iterations, the convergence of the design target optimization rate, and the convergence of the rate of change of two adjacent design targets.

9. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The iterative convergence criterion is: Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for the n-1th, nth, and n+1th iterations, TCR(k) 0 —Initial TCR results before optimization, —convergence threshold of optimization target reduction rate, ξ—convergence threshold of adjacent optimization target change rate.

10. An interface thermal conductivity distribution optimization design system for improving the contact thermal performance of an assembly interface, characterized in that: include: A microscopic morphology feature acquisition module is used to acquire the microscopic morphology features of the contact and heat dissipation surface of the component; The contact thermal performance numerical analysis model building module is used to build a contact thermal performance numerical analysis model based on the microscopic morphology characteristics of the contact heat dissipation surface of the component; Thermal conductivity distribution and contact thermal resistance calculation module, used to perform multiple iterative calculations on the thermal conductivity distribution of the design area using the contact thermal performance numerical analysis model to obtain the thermal conductivity distribution and contact thermal resistance; A judgment module, used to judge whether each iteration meets the iteration convergence criterion according to the thermal conductivity distribution and the contact thermal resistance; If the iteration convergence criteria are met, the thermal conductivity distribution and contact thermal resistance are output; If the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of using the contact thermal performance numerical analysis model to iterate the thermal conductivity distribution of the design area multiple times is returned.

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