CN113569520A - Optimization comparison method for thermal layout of electronic components of PCB (printed circuit board) - Google Patents

Optimization comparison method for thermal layout of electronic components of PCB (printed circuit board) Download PDF

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CN113569520A
CN113569520A CN202110841797.8A CN202110841797A CN113569520A CN 113569520 A CN113569520 A CN 113569520A CN 202110841797 A CN202110841797 A CN 202110841797A CN 113569520 A CN113569520 A CN 113569520A
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郭嘉宇
付康
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Zhongshan Dema Auto Parts Co ltd
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    • G06FELECTRIC DIGITAL DATA PROCESSING
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    • GPHYSICS
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    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2115/00Details relating to the type of the circuit
    • G06F2115/12Printed circuit boards [PCB] or multi-chip modules [MCM]
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Abstract

The invention discloses an optimization comparison method for thermal layout of electronic components of a PCB (printed circuit board); the method comprises the following steps: calculating a general expression of the temperature of each electronic component on the PCB according to a preset method; solving the temperature field according to a preset method and obtaining the thermal layout of electronic components on the PCB before and after optimization; obtaining temperature cloud pictures before and after optimization according to a preset comparison rule, and comparing the temperature cloud pictures before and after optimization; the optimization comparison method for the thermal layout of the electronic components of the PCB, disclosed by the invention, has the characteristics of capability of realizing global optimal solution, simple algorithm structure, simple operation, high calculation efficiency and the like.

Description

Optimization comparison method for thermal layout of electronic components of PCB (printed circuit board)
Technical Field
The invention relates to the technical field of PCB (printed circuit board), in particular to an optimization comparison method for thermal layout of electronic components of a PCB.
Background
In a PCB circuit containing heating elements such as a power tube, a core magnetic device, a power resistor and the like, the heat dissipation capability directly relates to the service life of the whole product; in the using process of the product, if the chip heat is too high and the chip heat cannot be dissipated, the equipment cannot normally operate. Therefore, finding a suitable layout of components is critical to the life of the device and the actual operation.
The temperature of components on a PCB is detected by using a thermal infrared imager in the prior art, and then the design of a PCB module is complicated; based on an intelligent optimization algorithm, the optimal component layout is calculated firstly, then the corresponding PCB module is designed, the efficiency is high, and the problem of equipment failure caused by overhigh chip temperature is solved.
At present, scholars at home and abroad invest great energy in the research on the thermal layout optimization of electronic components on a printed circuit board, and meanwhile, the research result of optimization algorithms is relatively rich, and a plurality of algorithms are mature day by day. The algorithm applied to PCB thermal layout optimization mainly comprises the following steps: the method comprises the following steps of (1) genetic algorithm, particle swarm algorithm, ant colony algorithm, simulated annealing algorithm and other improved algorithms, but the genetic algorithm has the characteristics of low search efficiency and incapability of obtaining a global optimal solution in practical application; the particle swarm algorithm is possibly applied to the problems that the algorithm is low in early precision, the optimal solution is easy to miss when the particle speed is too high, the convergence is not easy and the like; the ant colony algorithm also has a complex algorithm structure, and may finally fall into a local optimal solution, so that the calculation result is not globally optimal.
Disclosure of Invention
The embodiment of the application provides an optimization comparison method for thermal layout of electronic components of a PCB (printed circuit board), so as to realize the characteristics of global optimal solution, simple algorithm structure, simple operation, high calculation efficiency and the like.
In a first aspect, an embodiment of the present application provides an optimized comparison method for thermal layout of electronic components of a PCB, where the method includes the following steps:
calculating a general expression of the temperature of each electronic component on the PCB according to a preset method;
solving the temperature field according to a preset method and obtaining the thermal layout of electronic components on the PCB before and after optimization;
and obtaining the temperature cloud pictures before and after optimization according to a preset comparison rule, and comparing the temperature cloud pictures before and after optimization.
Further, the calculating a general expression of the temperature of each electronic component on the PCB according to a preset method includes:
and calculating a general expression of the temperature of each electronic component on the PCB by using a finite difference method.
Further, the calculating a general expression of the temperature of each electronic component on the PCB by using a finite difference method includes:
setting a PCB region with the length of L, the width of lambda and the thickness of delta, dividing the region into M x N sub-regions, and setting a region node as (M +1) x (N + 1);
acquiring a temperature expression of an internal center node;
acquiring a temperature expression of a boundary center node;
and acquiring a temperature expression of the edge node.
Further, the obtaining a temperature expression of the internal center node includes:
obtaining an internal center node, wherein the internal center node is a node on a component at the right middle position on the whole PCB, namely (M +1) × (N +1)/2, and the temperature expression of the internal center node is as follows:
Figure BDA0003179152670000021
wherein λ is the thermal conductivity of the plate; q (k, l) is the heat generation rate per unit volume of the node of the ith row and the ith column; epsilon is the emissivity of the flat plate; σ is the Stefan-Boltzmann radiation constant; h is the heat convection heat transfer coefficient between the flat plate and the surrounding air; tsurr is the temperature of the surrounding object; t ∞ is the temperature of air, and Tsurr ═ T ∞ can be taken as usual; t isk+1,l,Tk,l,Tk-1,l,Tk,l+1,Tk,l-1The temperatures of the components are correspondingly numbered, and delta is the thickness of the flat plate.
Further, the obtaining a temperature expression of the boundary center node includes:
obtaining a boundary central node, wherein the boundary central node is a node at the middle position of the boundary on the whole PCB, namely a node of an even number element in the M x N electronic layout, and the temperature expression of the boundary central node obtained according to a finite difference method is as follows:
Figure BDA0003179152670000022
wherein q (i, j) refers to the heat generation rate per unit volume of the ith row and jth column element.
Further, the obtaining a temperature expression of the edge node includes:
obtaining edge nodes which are nodes of the corner positions on the whole PCB, namely nodes of odd-numbered elements (except internal center nodes) in the layout of the M x N electronic elements, wherein the temperature expression of the edge nodes obtained according to a finite difference method is as follows:
Figure BDA0003179152670000031
where q (m, n) refers to the heat generation rate per unit volume of the element in the mth row and nth column.
Further, the solving of the temperature field and the obtaining of the thermal layout of the electronic components on the PCB before and after the optimization according to the preset method includes:
and solving the temperature field by using MATLAB programming and obtaining the thermal layout of the electronic components on the PCB before and after optimization.
Further, the utilizing MATLAB programming to realize the solution of the temperature field and obtain the thermal layout of the electronic components on the PCB before and after the optimization includes:
the first step, initialization process: when the algorithm starts, an initial control parameter cont is set, the iteration number iter is 100, and an initial solution x is randomly selected and generated, which is the initial solution of the whole algorithm iteration.
Step two, under each initial control parameter cont, carrying out iter-1, 2,3.. 100 times, and circularly carrying out the operation from the step three to the step six;
step three, randomly generating a new solution x';
a fourth step of calculating a difference between the previous and subsequent evaluation functions f (x), wherein the increment f (x') -f (x);
fifthly, if the increment f is less than 0, accepting a new solution x 'in percentage at the moment, and taking the new solution as a current solution, otherwise, discarding the new solution or accepting the new solution x' as a new current solution by using a random number with probability greater than (0, 1);
sixthly, ending the algorithm if the algorithm meets the termination condition, wherein the final current solution is an approximately optimal solution obtained by simulating the annealing algorithm, and terminating the program at the moment;
in the seventh step, cont is gradually decreased, and cont > is 0, and then, the second step is skipped.
Further, the obtaining of the temperature cloud images before and after optimization according to a preset comparison rule and the comparison of the temperature cloud images before and after optimization include:
and performing analog simulation by using three-dimensional thermal simulation software Icepak to obtain temperature cloud charts before and after optimization, and comparing the temperature cloud charts before and after optimization.
Further, the simulation and comparison of the results before and after the optimization by using the three-dimensional thermal simulation software Icepak include:
establishing a corresponding thermal analysis model in the Icepak, sequentially carrying out meshing and checking whether the meshing is correct or not;
if the model is correct, setting the boundary condition of the model;
setting solving control parameters and solving a temperature field to obtain a temperature cloud picture, and carrying out specific heat layout optimization on the conditions before and after optimization according to the temperature cloud picture.
The method comprises the steps of calculating a general expression of the temperature of each electronic component on the PCB according to a preset method; solving the temperature field according to a preset method and obtaining the thermal layout of electronic components on the PCB before and after optimization; obtaining temperature cloud pictures before and after optimization according to a preset comparison rule, and comparing the temperature cloud pictures before and after optimization; the method has the characteristics of realization of global optimal solution, simple algorithm structure, simple operation, high calculation efficiency and the like.
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Fig. 1 is a flowchart of an optimization comparison method for thermal layout of electronic components of a PCB according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of the simulated annealing algorithm provided by the embodiment of the present application for optimizing the thermal layout of the electronic components of the PCB;
FIG. 3 is a flow chart of a MATLAB programming implementation to obtain a PCB temperature field and optimize layout provided by an embodiment of the present application;
FIG. 4 is a schematic diagram illustrating division of a grid node obtained by calculating a temperature field by using a finite difference method according to an embodiment of the present application;
FIG. 5 is a graph one of the results of an optimal layout obtained using MATLAB as provided by an embodiment of the present application;
FIG. 6 is a graph II of the results of an optimal layout obtained using MATLAB as provided by an embodiment of the present application;
FIG. 7 is a third graph of the results of an optimal layout obtained using MATLAB as provided by an embodiment of the present application;
FIG. 8 is a diagram of a finite element model of an object embodying the present invention provided in an embodiment of the present application;
FIG. 9 is a general flow chart for operation with the three-dimensional thermal simulation software Icepak provided by an embodiment of the present application;
FIG. 10 is a temperature cloud before layout optimization as provided by an embodiment of the present application;
fig. 11 is a temperature cloud diagram after layout optimization provided in the embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Fig. 1 is a flowchart of an optimization comparison method for thermal layout of electronic components of a PCB provided in an embodiment of the present application. Referring to fig. 1, the method for optimizing and comparing the thermal layout of the electronic components of the PCB comprises the following steps:
and step 110, calculating a general expression of the temperature of each electronic component on the PCB according to a preset method.
Specifically, a general expression of the temperature of each electronic component on the PCB is calculated by using a finite difference method.
Optionally, a general expression of a temperature equation of the electronic component is obtained first by using a finite difference method, the essence of the finite difference method is to convert a continuous physical problem into discretization solution, and a differential quotient is used to replace a derivative quotient in the solution process. The solution of the rectangular block flat plate temperature field belongs to a continuous physical problem, and the numerical solution of the temperature field cannot be directly carried out. By utilizing the idea of finite difference method, the rectangular block is firstly divided into areas to form a plurality of small grid areas and a plurality of grid nodes, and the temperature values of the grid nodes are used for replacing the temperature field temperature of the surrounding areas, so that when the grid division is fine enough, the discrete node temperature value solving problem approaches to the solving value of the continuous physical problem.
The general expression for calculating the temperature of each electronic component on the PCB by using the finite difference method comprises the following steps:
step 1101, setting a PCB region with a length of L, a width of λ, and a thickness of δ, dividing the region into M × N sub-regions, and setting a region node as (M +1) × (N + 1).
As shown in fig. 4, for a PCB region with a length L, a width L', and a thickness δ, the region may be divided into MxN sub-regions, and then there are (M +1) × (N +1) nodes in the region, and a finite difference method is used in the region to calculate the temperature of each node in the region. The distance between the horizontal and vertical coordinates of two adjacent components is the temperature of the mth row and the nth column, and q is the power of the component. The finer the grid division is, the more accurate the calculation result is, but the finer the grid is, the larger the calculation amount is, when the calculation result is within the error allowable range, the grid does not need to be refined continuously, and the calculation result is an acceptable approximate solution at this moment.
Step 1102, obtaining a temperature expression of an internal center node, specifically, obtaining the internal center node, where the internal center node is a node on a component at the middle position on the whole PCB, that is, (M +1) × (N +1)/2, and the temperature expression of the internal center node is obtained as follows:
Figure BDA0003179152670000061
wherein λ is the thermal conductivity of the plate; q (k, l) is the heat generation rate per unit volume of the node of the ith row and the ith column; epsilon is the emissivity of the flat plate; σ is the Stefan-Boltzmann radiation constant; h is the heat convection heat transfer coefficient between the flat plate and the surrounding air; tsurr is the temperature of the surrounding object; t ∞ is the temperature of air, and Tsurr ═ T ∞ can be taken as usual; t isk+1,l,Tk,l,Tk-1,l,Tk,l+1,Tk,l-1The temperatures of the components are correspondingly numbered, and delta is the thickness of the flat plate.
Step 1103, obtaining a temperature expression of the boundary center node, specifically, obtaining the boundary center node, where the boundary center node is a node at the middle position of the boundary on the whole PCB, that is, a node of an even number element in the M × N electronic layout, and the temperature expression of the boundary center node obtained according to the finite difference method is:
Figure BDA0003179152670000062
wherein q (i, j) refers to the heat generation rate per unit volume of the ith row and jth column element.
Step 1104, obtaining a temperature expression of an edge node, specifically, obtaining an edge node, where the edge node is a node at a corner position on the whole PCB, that is, a node (excluding an inner center node) of an odd-numbered element in the layout of the M × N electronic elements, and the temperature expression of the edge node obtained according to the finite difference method is:
Figure BDA0003179152670000063
where q (m, n) refers to the heat generation rate per unit volume of the element in the mth row and nth column.
For example, taking 3 × 3 component layout as an example, the components are numbered 1, 2.. 9 sequentially from left to right and from top to bottom, and the nodes of 9 components on the PCB board can be roughly divided into an internal center node, a boundary center node and an edge node, considering that the heat transfer manner of electronic components at different positions is different.
The internal center node is a node on a component at the right middle position on the whole PCB, namely a 5 th component in a 3 x3 electronic layout, and a temperature expression of the internal center node can be obtained by a finite difference method in consideration of three heat transfer conditions of heat conduction, heat convection and heat radiation:
Figure BDA0003179152670000071
where λ is the thermal conductivity of the plate in W/m-K, which is 0.3W/m-K for FR4, and q (2,2) is the heat generation rate per unit volume of the 2 nd node in row 2 in W/m3. ε is the emissivity of the plate, and σ is the Stefan-Boltzmann radiation constant, and the magnitude is 5.67 x 10-8w/m2-K4H is the heat convection heat transfer coefficient of the flat plate and the surrounding air, and the unit is W/m2-K, the value range is 3-25W/m2K, Tsurr is the temperature of the surrounding object, T ∞ is the temperature of air, and Tsurr ∞ and T ∞ can be taken as the temperature of air6,T5,T4,T2,T8The temperatures of the components are correspondingly numbered, delta is the thickness of the flat plate, and the unit is m.
The boundary center node is a node at the middle position of the boundary on the whole PCB, that is, a node of the 2 nd, 4 th, 6 th and 8 th elements in the 3 × 3 electronic layout, taking the 6 th element as an example, a general expression of the node temperature obtained according to the finite difference method is as follows:
Figure BDA0003179152670000072
where q (2,3) refers to the heat generation rate per unit volume of row 2, column 3 elements, i.e., element number 6, in W/m3
The edge node is a node at a corner position on the whole PCB, that is, a node of the 1 st, 3 rd, 7 th and 9 th components in the layout of 3 × 3 electronic components, taking the 3 rd component as an example, a general expression of the node temperature obtained according to the finite difference method is as follows:
Figure BDA0003179152670000081
in the formula, q (1,3) means the heat generation rate per unit volume of the element at the 1 st row and the 3 rd column, that is, the element No. 3, and has a unit of W/m3
And 120, solving the temperature field according to a preset method and obtaining the thermal layout of the electronic components on the PCB before and after optimization.
Specifically, the MATLAB programming is utilized to realize the solution of the temperature field and obtain the thermal layout of the electronic components on the PCB before and after optimization.
Referring to fig. 2, the using MATLAB programming to solve the temperature field and obtain the thermal layout of the electronic components on the PCB before and after optimization includes:
the first step, initialization process: when the algorithm starts, an initial control parameter cont is set, the iteration number iter is 100, and an initial solution x is randomly selected and generated, which is the initial solution of the whole algorithm iteration.
Step two, under each initial control parameter cont, carrying out iter-1, 2,3.. 100 times, and circularly carrying out the operation from the step three to the step six;
step three, randomly generating a new solution x';
a fourth step of calculating a difference between the previous and subsequent evaluation functions f (x), wherein the increment f (x') -f (x);
fifthly, if the increment f is less than 0, accepting a new solution x 'in percentage at the moment, and taking the new solution as a current solution, otherwise, discarding the new solution or accepting the new solution x' as a new current solution by using a random number with probability greater than (0, 1);
sixthly, ending the algorithm if the algorithm meets the termination condition, wherein the final current solution is an approximately optimal solution obtained by simulating the annealing algorithm, and terminating the program at the moment;
in the seventh step, cont is gradually decreased, and cont > is 0, and then, the second step is skipped.
The solution space is a set of arrangement modes of all electronic components on the PCB, and taking a 3 × 3 electronic component layout as an example, the generated solution space output should be in a matrix form of 3 × 3, and the value of each position should change according to the solution space generated after each iteration, and the value of each position represents the power of the component at the position; the research aims to find out a component layout so that the temperature of the whole PCB is the lowest, and therefore the global maximum temperature Tmax of electronic components on the PCB during working is taken as an objective function of the algorithm.
For example, for the generation and reception rules of the new solution, taking 9 elements as an example, the current solution is transformed by a binary transformation method to generate the new solution, that is, simply interchanging positions of elements in any two positions to generate the new solution, such as x ═ { x1, x2, x 3; x4, x5, x 6; x7, x8, x9, if x2 and x6 are interchanged randomly, a new solution is generated: x' ═ { X1, X6, X3; x4, X5, X2; x7, X8, X9 }. Whether the new solution is received or not is judged according to a Metropolis criterion of a simulated annealing algorithm, the solution is directly received better than the current solution, and the Metropolis criterion is shown in a formula (4) for poor new solutions with certain probability.
Figure BDA0003179152670000091
If Ei < Ej, accepting j as the current state; otherwise, if the probability P ═ exp [ - (Ei-Ej)/KT ] is greater than the random number in the interval of [0,1 ], the state j is still accepted as the current state; if not, the state i is reserved as the current state. Wherein E is the internal energy in a certain state at the temperature T, Ei-Ej is the change quantity of the internal energy, and K is a Boltzmann constant.
As shown in fig. 3, firstly, randomly generating a layout, and calculating a temperature vector T of 9 elements by using a general equation about temperature differences of 9 elements obtained in step 1 and simply programming MATLAB (T1, T2.. T9); taking the highest temperature as the highest temperature of the whole PCB, recording the current layout as the optimal layout, and taking the current highest temperature Tpremax as the optimal temperature; secondly, randomly generating another layout on the basis of the current layout by using a binary method, calculating a temperature vector and a highest temperature Tmax under the layout, judging whether the Tmax is smaller than the Tpremax, if so, receiving the layout as an optimal layout, and receiving the Tmax as an optimal temperature; if not, judging whether to receive the layout according to the Metropolis criterion; finally, judging whether a termination condition is reached, if not, performing cooling annealing, then performing iterative calculation on the optimal layout and the optimal temperature, and if so, outputting the optimal layout and the optimal temperature; the cooling annealing determines the accuracy of the whole algorithm, and is determined by an initial parameter cont and an attenuation factor, wherein the attenuation factor is generally set to be between 0.90 and 0.99, the initial parameter cont is generally selected to be large enough, and the iteration number iter of the internal Monte Carlo simulation is set to be 100.
Fig. 5 to 7 are a temperature field vector result graph of 3 × 3 electronic component layout on a PCB obtained by MATLAB programming, and result graphs before and after layout optimization, where an ambient temperature is set to 20 ℃, a thermal conductivity coefficient is set to λ 0.3W/M-K, and a default division node grid is a square: the distance between the horizontal and vertical coordinates of two adjacent components is equal, delta X-delta Y-1 CM-0.01M, epsilon is the emissivity of the flat plate, the value is 0.5,
wherein σ is Stefan-Boltzmann radiation constant of 5.67 × 10-8W/m2-K4H is the heat convection heat transfer coefficient of the flat plate and the surrounding air, and the unit is W/m2-K, of 10W/m2-K, plate thickness δ 3.4mm 0.0034 m; in the figure, S is the previous layout, T is the highest temperature of the previous layout, S2 is the new layout generated on the basis of S, T is the temperature vector under the S2 layout, Tpremax is the highest temperature of the PCB under the S2 layout, and dC is the difference compared with the previous layout, because dC<And 0, receiving the S2 layout as the optimal layout, wherein T is the optimal temperature, and the final result of the optimal layout is that S2 is the optimal layout under the environment temperature of 20 ℃, and the value of Tpremax is the optimal temperature.
And step 130, obtaining the temperature cloud pictures before and after optimization according to a preset comparison rule, and comparing the temperature cloud pictures before and after optimization.
Specifically, simulation is carried out by using three-dimensional thermal simulation software Icepak to obtain temperature cloud charts before and after optimization, and the temperature cloud charts before and after optimization are compared.
The simulation and comparison of the results before and after optimization by using the three-dimensional thermal simulation software Icepak comprise:
step 1301, establishing a corresponding thermal analysis model in the Icepak, sequentially carrying out meshing and checking whether the meshing is correct or not;
step 1302, if the result is correct, setting a boundary condition of the model;
and step 1303, setting solving control parameters and solving the temperature field to obtain a temperature cloud picture, and carrying out specific heat layout optimization on the conditions before and after optimization according to the temperature cloud picture.
In order to further verify the accuracy of the result, finally, a three-dimensional thermal simulation software ICEPAK is used for simulation, an ICEPAK self-contained block module is used for simulating electronic components, the sizes and the intervals of the components are set according to the conditions in the step 2, and finally, an obtained finite element three-dimensional simulation model is shown in fig. 8, wherein 1 is a PCB model, 2 is an electronic component, and Q1 and Q2.
FIG. 9 is a general computational flow diagram of thermal simulation, which mainly includes: establishing a geometric model, dividing grids, calculating, solving and setting, and post-processing a calculation result.
Setting the ambient temperature in thermal simulation to be 20 ℃, setting the flow model of air to be a turbulence model, selecting readable two equalizations for model calculation, simultaneously turning on radiation heat exchange and gravity influence factors, setting momentum relaxation factors to be 0.7 and pressure relaxation factors to be 0.3 according to software setting requirements, solving and calculating the calculation precision by adopting single precision, setting the iteration number to be 1000, setting the energy equation convergence residual error to be 0.001, setting a temperature monitoring point at the geometric center point of each chip surface, and finally obtaining a temperature cloud picture before layout optimization (figure 10) and a temperature cloud picture after layout optimization (figure 11). For the global maximum temperature, the heat distribution after optimization is reduced compared with the heat distribution before optimization, and the heat dissipation amount is increased through the heat distribution optimization.
According to the power of the existing components, the layout of a plurality of components is obtained by using a finite difference method and a simulated annealing algorithm, the highest temperature of the whole PCB is calculated, then the layout which enables the temperature of the whole PCB to be the lowest is found out by using the simulated annealing algorithm, and finally, the three-dimensional thermal simulation software Icepak is used for further verification. The research method provided by the invention avoids the condition that the whole device fails due to the fact that the temperature of a certain component on the PCB is higher. In addition, the PCB temperature field obtained according to the finite difference method takes the three conditions of heat conduction, heat convection and heat radiation into consideration, and the condition of temperature deviation existing in practical application is also avoided. The obtained optimal layout can provide a certain theoretical basis for actual PCB plate making, avoids the possibility of higher temperature of the whole PCB in blind plate making, and has higher engineering research value.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.

Claims (10)

1. An optimization comparison method for thermal layout of electronic components of a PCB (printed circuit board) is characterized by comprising the following steps:
calculating a general expression of the temperature of each electronic component on the PCB according to a preset method;
solving the temperature field according to a preset method and obtaining the thermal layout of electronic components on the PCB before and after optimization;
and obtaining the temperature cloud pictures before and after optimization according to a preset comparison rule, and comparing the temperature cloud pictures before and after optimization.
2. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 1, wherein the calculating the general expression of the temperature of each electronic component on the PCB according to the preset method comprises:
and calculating a general expression of the temperature of each electronic component on the PCB by using a finite difference method.
3. The method for optimizing and comparing the thermal layout of the electronic components of the PCB as claimed in claim 2, wherein the calculating the general expression of the temperature of each electronic component on the PCB by using the finite difference method comprises:
setting a PCB region with the length of L, the width of lambda and the thickness of delta, dividing the region into M x N sub-regions, and setting a region node as (M +1) x (N + 1);
acquiring a temperature expression of an internal center node;
acquiring a temperature expression of a boundary center node;
and acquiring a temperature expression of the edge node.
4. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 3, wherein the obtaining the temperature expression of the internal center node comprises:
obtaining an internal center node, wherein the internal center node is a node on a component at the right middle position on the whole PCB, namely (M +1) × (N +1)/2, and the temperature expression of the internal center node is as follows:
Figure FDA0003179152660000011
wherein λ is the thermal conductivity of the plate; q (k, l) is the heat generation rate per unit volume of the node of the ith row and the ith column; epsilon is the emissivity of the flat plate; σ is the Stefan-Boltzmann radiation constant; h is the heat convection heat transfer coefficient between the flat plate and the surrounding air; tsurr is the temperature of the surrounding object; t ∞ is the temperature of air, and Tsurr ═ T ∞ can be taken as usual; t isk+1,l,Tk,l,Tk-1,l,Tk,l+1,Tk,l-1The temperatures of the components in the corresponding rows and columns are respectively, and delta is the thickness of the flat plate.
5. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 3, wherein the obtaining the temperature expression of the boundary center node comprises:
obtaining a boundary central node, wherein the boundary central node is a node at the middle position of the boundary on the whole PCB, namely a node of an even number element in the M x N electronic layout, and an expression of the boundary central node obtained according to a finite difference method is as follows:
Figure FDA0003179152660000021
wherein q (i, j) refers to the heat generation rate per unit volume of the ith row and jth column element.
6. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 3, wherein the obtaining the temperature expression of the edge node comprises:
obtaining edge nodes, wherein the edge nodes are nodes at the corner positions on the whole PCB, namely nodes (except internal center nodes) of odd-numbered elements in the layout of the M x N electronic elements, and the temperature expression of the edge nodes obtained according to a finite difference method is as follows:
Figure FDA0003179152660000022
where q (m, n) refers to the heat generation rate per unit volume of the element in the mth row and nth column.
7. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 1, wherein the step of solving the temperature field according to a preset method and obtaining the thermal layout of the electronic components on the PCB before and after optimization comprises the following steps:
and solving the temperature field by using MATLAB programming and obtaining the thermal layout of the electronic components on the PCB before and after optimization.
8. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 7, wherein the step of solving the temperature field by using MATLAB programming and obtaining the thermal layout of the electronic components on the PCB before and after the optimization comprises the following steps:
the first step, initialization process: when the algorithm starts, setting an initial control parameter cont, setting the iteration number iter as 100, and randomly selecting and generating an initial solution x which is the initial solution of the whole algorithm iteration;
step two, under each initial control parameter cont, carrying out iter-1, 2,3.. 100 times, and circularly carrying out the operation from the step three to the step six;
step three, randomly generating a new solution x';
a fourth step of calculating a difference between the previous and subsequent evaluation functions f (x), wherein the increment f (x') -f (x);
fifthly, if the increment f is less than 0, accepting a new solution x 'in percentage at the moment, and taking the new solution as a current solution, otherwise, discarding the new solution or accepting the new solution x' as a new current solution by using a random number with probability greater than (0, 1);
sixthly, ending the algorithm if the algorithm meets the termination condition, wherein the final current solution is an approximately optimal solution obtained by simulating the annealing algorithm, and terminating the program at the moment;
in the seventh step, cont is gradually decreased, and cont > is 0, and then, the second step is skipped.
9. The method for optimizing and comparing the thermal layout of the electronic components of the PCB according to claim 1, wherein the step of obtaining the temperature cloud images before and after optimization according to a preset comparison rule and comparing the temperature cloud images before and after optimization comprises the steps of:
and performing analog simulation by using three-dimensional thermal simulation software Icepak to obtain temperature cloud charts before and after optimization, and comparing the temperature cloud charts before and after optimization.
10. The method for optimizing and comparing the thermal layout of the electronic components of the PCB of claim 9, wherein the simulating and comparing the results before and after the optimizing by using the three-dimensional thermal simulation software Icepak comprises:
establishing a corresponding thermal analysis model in the Icepak, sequentially carrying out meshing and checking whether the meshing is correct or not;
if the model is correct, setting the boundary condition of the model;
setting solving control parameters and solving a temperature field to obtain a temperature cloud picture, and carrying out specific heat layout optimization on the conditions before and after optimization according to the temperature cloud picture.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115460895A (en) * 2022-11-10 2022-12-09 武汉至驱动力科技有限责任公司 Electronic water pump controller heat dissipation method based on temperature field image information

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115460895A (en) * 2022-11-10 2022-12-09 武汉至驱动力科技有限责任公司 Electronic water pump controller heat dissipation method based on temperature field image information
CN115460895B (en) * 2022-11-10 2023-02-17 武汉至驱动力科技有限责任公司 Electronic water pump controller heat dissipation method based on temperature field image information

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