Comparative optimization methods for thermal layout of electronic components on PCB boards

Abstract

The present invention discloses a method for optimizing and comparing the thermal layout of electronic components on a PCB. The method comprises: calculating a general expression for the temperature of each electronic component on the PCB according to a preset method; solving a temperature field according to the preset method and obtaining the thermal layout of the electronic components on the PCB before and after optimization; obtaining temperature cloud maps before and after optimization according to preset comparison rules, and comparing the temperature cloud maps before and after optimization. The method for optimizing and comparing the thermal layout of electronic components on a PCB disclosed by the present invention can achieve a global optimal solution, has a simple algorithm structure, is easy to use, and has high computational efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of PCB boards, and in particular to a method for optimizing and comparing the thermal layout of electronic components on a PCB board. Background Art

[0002] In PCB circuits containing heat-generating components such as power transistors, core magnetic devices, and power resistors, heat dissipation capacity is directly related to the product's service life. During product use, if excessive heat from the chip cannot be dissipated, the device will not function properly. Therefore, finding a suitable component layout is crucial to the device's lifespan and actual operation.

[0003] The traditional method of using infrared thermal imagers to detect the temperature of components on the PCB and then designing the PCB module is rather cumbersome. Based on the intelligent optimization algorithm, the optimal component layout is calculated first and then the corresponding PCB module is designed. This is more efficient and avoids the problem of equipment failure caused by excessive chip temperature.

[0004] Currently, scholars at home and abroad have devoted significant effort to the research of thermal layout optimization for electronic components on printed circuit boards (PCBs). Optimization algorithm research has also yielded relatively fruitful results, and many algorithms are becoming increasingly mature. The main algorithms used for PCB thermal layout optimization include genetic algorithms, particle swarm optimization algorithms, ant colony algorithms, simulated annealing algorithms, and other improved algorithms. However, in practical applications, genetic algorithms suffer from low search efficiency and the inability to obtain a global optimal solution. Particle swarm optimization algorithms can suffer from low early-stage accuracy, the tendency to miss the optimal solution when particle velocity is too high, and non-convergence. Ant colony algorithms also suffer from complex algorithmic structures and may eventually fall into local optimal solutions, resulting in calculation results that are not globally optimal. Summary of the Invention

[0005] The embodiment of the present application provides an optimization and comparison method for the thermal layout of electronic components on a PCB board, so as to achieve the characteristics of a global optimal solution, a simple algorithm structure, easy to use, and high computational efficiency.

[0006] In a first aspect, an embodiment of the present application provides a method for optimizing and comparing the thermal layout of electronic components on a PCB board, the method comprising the following steps:

[0007] Calculate the general expression of the temperature of each electronic component on the PCB board according to the preset method;

[0008] Solve the temperature field according to the preset method and obtain the thermal layout of electronic components on the PCB before and after optimization;

[0009] The temperature cloud maps before and after optimization are obtained according to the preset comparison rules, and the temperature cloud maps before and after optimization are compared.

[0010] Furthermore, the general expression for calculating the temperature of each electronic component on the PCB board according to a preset method includes:

[0011] The general expression for calculating the temperature of each electronic component on the PCB board is calculated using the finite difference method.

[0012] Furthermore, the general expression for calculating the temperature of each electronic component on the PCB board using the finite difference method includes:

[0013] Set up a PCB area with a length of L, a width of λ, and a thickness of δ. Divide the area into M*N sub-areas, and the area nodes are (M+1)*(N+1).

[0014] Get the temperature expression of the internal central node;

[0015] Get the temperature expression of the boundary center node;

[0016] Get the temperature expression of the edge node.

[0017] Furthermore, the obtaining of the temperature expression of the internal central node includes:

[0018] Get the internal center node, which is the node on the component in the middle of the entire PCB board, that is, (M+1)*(N+1) / 2. The temperature expression of the internal center node is:

[0019]

[0020] Where λ is the thermal conductivity of the plate; q(k,l) is the heat generation rate per unit volume of the node in the kth row and lth column; ε is the emissivity of the plate; σ is the Stefan-Boltzmann radiation constant; h is the heat convection coefficient between the plate and the surrounding air; Tsurr is the temperature of the surrounding objects; T∞ is the temperature of the air, which can usually be taken as Tsurr = T∞; T k+1,l ,T k,l ,T k-1,l ,T k,l+1 ,T k,l-1 are the temperatures of the components with corresponding numbers, and δ is the thickness of the plate.

[0021] Furthermore, the temperature expression of the boundary center node is obtained, including:

[0022] Get the boundary center node. The boundary center node is the node in the middle of the boundary of the entire PCB board, that is, the node of the even-numbered components in the M*N electronic layout. The temperature expression of the boundary center node obtained by the finite difference method is:

[0023]

[0024] Here, q(i,j) refers to the heat generation rate per unit volume of the element in the i-th row and j-th column.

[0025] Furthermore, the step of obtaining the temperature expression of the edge node includes:

[0026] Obtain edge nodes, which are nodes at the corner positions of the entire PCB board, that is, the nodes of the odd-numbered components (excluding the internal center node) in the M*N electronic component layout. The temperature expression of the edge nodes obtained by the finite difference method is:

[0027]

[0028] Where q(m,n) refers to the heat generation rate per unit volume of the element in the mth row and nth column.

[0029] Furthermore, the method of solving the temperature field according to a preset method and obtaining the thermal layout of electronic components on the PCB before and after optimization includes:

[0030] MATLAB programming is used to solve the temperature field and obtain the thermal layout of electronic components on the PCB board before and after optimization.

[0031] Furthermore, the method of using MATLAB programming to solve the temperature field and obtain the thermal layout of electronic components on the PCB before and after optimization includes:

[0032] The first step is the initialization process: at the beginning of the algorithm, the initial control parameter cont is set, the number of iterations iter = 100, and an initial solution x is randomly selected to generate, which is the starting solution of the entire algorithm iteration.

[0033] In the second step, under each initial control parameter cont, perform iter=1,2,3...100 times, and repeat the operations from the third to the sixth step in a loop;

[0034] The third step is to randomly generate a new solution x';

[0035] The fourth step is to calculate the difference between the evaluation function f(x) before and after, where the increment f = f(x') - f(x);

[0036] Step 5: If the increment f < 0, then the new solution x' is accepted with 100% probability and is taken as the current solution. Otherwise, the new solution is discarded or the new solution x' is accepted as the new current solution with a probability greater than a random number in (0, 1).

[0037] Step 6: If the algorithm meets the termination condition, the algorithm ends. The final current solution is the approximate optimal solution obtained by the simulated annealing algorithm, and the program is terminated at this time.

[0038] In the seventh step, cont gradually decreases, and cont>=0, then jumps to the second step.

[0039] Furthermore, obtaining the temperature cloud maps before and after optimization according to a preset comparison rule and comparing the temperature cloud maps before and after optimization include:

[0040] The three-dimensional thermal simulation software Icepak was used to perform simulations to obtain the temperature cloud maps before and after optimization, and the temperature cloud maps before and after optimization were compared.

[0041] Furthermore, the simulation is performed using the three-dimensional thermal simulation software Icepak and the results before and after optimization are compared, including:

[0042] Establish the corresponding thermal analysis model in Icepak, perform mesh division in sequence and check whether the mesh division is correct;

[0043] If correct, set the boundary conditions of the model;

[0044] The control parameters for the solution are set and the temperature field is solved to obtain a temperature cloud map, and the conditions before and after the thermal layout optimization are compared based on the temperature cloud map.

[0045] The embodiment of the present application calculates a general expression for the temperature of each electronic component on a PCB board according to a preset method; solves the temperature field according to the preset method and obtains the thermal layout of the electronic components on the PCB board before and after optimization; obtains temperature cloud maps before and after optimization according to preset comparison rules, and compares the temperature cloud maps before and after optimization; thereby achieving a global optimal solution, a simple algorithm structure, easy to use, and high computational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart of a method for optimizing and comparing thermal layout of electronic components on a PCB board provided in an embodiment of the present application;

[0047] Figure 2 This is a flow chart of optimizing the thermal layout of electronic components on a PCB board using a simulated annealing algorithm provided in an embodiment of the present application;

[0048] Figure 3 This is a flowchart of obtaining the PCB temperature field and optimizing the layout through MATLAB programming provided in an embodiment of the present application;

[0049] Figure 4 This is a schematic diagram of grid node division for calculating temperature field using the finite difference method provided in an embodiment of the present application;

[0050] Figure 5 This is the result of the optimal layout obtained using MATLAB provided in the embodiment of this application Figure 1 ;

[0051] Figure 6 This is the result of the optimal layout obtained using MATLAB provided in the embodiment of this application Figure 2 ;

[0052] Figure 7 This is the result of the optimal layout obtained using MATLAB provided in the embodiment of this application Figure 3 ;

[0053] Figure 8 It is a finite element model diagram of an object implemented by the present invention provided in the embodiment of the present application;

[0054] Figure 9 This is a general flow chart of the operation using the three-dimensional thermal simulation software Icepak provided in an embodiment of the present application;

[0055] Figure 10 This is a temperature cloud map before layout optimization provided in an embodiment of the present application;

[0056] Figure 11 This is a temperature cloud map after layout optimization provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. It should also be noted that, for ease of description, only parts related to the present application, not all of the contents, are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0058] Figure 1 This is a flow chart of a method for optimizing and comparing the thermal layout of electronic components on a PCB board provided in an embodiment of the present application. Figure 1 A method for optimizing and comparing the thermal layout of electronic components on a PCB board comprises the following steps:

[0059] Step 110: Calculate a general expression for the temperature of each electronic component on the PCB board according to a preset method.

[0060] Specifically, the finite difference method is used to calculate the general expression of the temperature of each electronic component on the PCB board.

[0061] Optionally, the finite difference method can be used to first obtain the general expression of the temperature equation of the electronic component. The essence of the finite difference method is to transform a continuous physical problem into a discrete solution, and the difference quotient is used instead of the differential quotient in the solution process. The solution to the temperature field of the rectangular block plate is a continuous physical problem, and its temperature field cannot be directly solved numerically. Using the idea of ​​the finite difference method, the rectangular block is first divided into regions to form many small grid regions and many grid nodes. The temperature value of the grid node is used to replace the temperature field temperature of the surrounding area. Therefore, when the grid division is fine enough, the discrete node temperature value solution is close to the solution value of the continuous physical problem.

[0062] The general expression for calculating the temperature of each electronic component on the PCB using the finite difference method includes:

[0063] Step 1101: Set a PCB area with a length of L, a width of λ, and a thickness of δ, and divide the area into M*N sub-areas, with area nodes being (M+1)*(N+1).

[0064] like Figure 4 As shown, for a PCB area with a length of L, a width of L', and a thickness of δ, the area can be divided into MxN sub-areas. This area then has (M+1)*(N+1) nodes. The finite difference method is used to calculate the temperature of each node in this area. Here, is the distance between the horizontal and vertical coordinates of two adjacent components, is the temperature in the mth row and nth column, and q is the power of the component. A finer mesh yields more accurate calculations, but the computational complexity increases. When the calculation result is within the allowable error range, the mesh does not need to be further refined, and the result is an acceptable approximate solution.

[0065] Step 1102: Obtain a temperature expression for an internal central node. Specifically, obtain the internal central node, which is a node on a component located in the middle of the entire PCB board, that is, (M+1)*(N+1) / 2. The temperature expression for the internal central node is:

[0066]

[0067] Where λ is the thermal conductivity of the plate; q(k,l) is the heat generation rate per unit volume of the node in the kth row and lth column; ε is the emissivity of the plate; σ is the Stefan-Boltzmann radiation constant; h is the heat convection coefficient between the plate and the surrounding air; Tsurr is the temperature of the surrounding objects; T∞ is the temperature of the air, which can usually be taken as Tsurr = T∞; T k+1,l ,Tk,l ,T k-1,l ,T k,l+1 ,T k,l-1 are the temperatures of the components with corresponding numbers, and δ is the thickness of the plate.

[0068] Step 1103: Obtain a temperature expression for the boundary center node. Specifically, obtain the boundary center node. The boundary center node is the node at the middle position of the boundary of the entire PCB board, that is, the node of the even-numbered components in the M*N electronic layout. The temperature expression for the boundary center node obtained by the finite difference method is:

[0069]

[0070] Here, q(i,j) refers to the heat generation rate per unit volume of the element in the i-th row and j-th column.

[0071] Step 1104: Obtain a temperature expression for an edge node. Specifically, obtain an edge node. The edge node is a node at a corner position on the entire PCB board, that is, a node of an odd-numbered component in an M*N electronic component layout (excluding the inner center node). The temperature expression for the edge node obtained using the finite difference method is:

[0072]

[0073] Where q(m,n) refers to the heat generation rate per unit volume of the element in the mth row and nth column.

[0074] For example, taking a 3*3 component layout as an example, the components are numbered 1, 2...9 in order from left to right and from top to bottom. Considering the different ways of heat transfer in electronic components at different positions, the nodes of the 9 components on the PCB board can be roughly divided into internal center nodes, boundary center nodes and edge nodes.

[0075] The internal center node is the node on the component in the middle of the entire PCB board, which is the fifth component in the 3*3 electronic layout. Considering the three heat transfer conditions of heat conduction, heat convection and heat radiation, the temperature expression of the internal center node can be obtained using the finite difference method:

[0076]

[0077] Where λ is the thermal conductivity of the plate in W / mK. For FR4, this value is 0.3W / mK. q(2,2) is the heat generation rate per unit volume of the node in the second row and second column in W / m 3 ε is the emissivity of the plate, which is between 0 and 1, and σ is the Stefan-Boltzmann radiation constant, which is 5.67*10 -8 w / m 2-K 4 , h is the heat convection heat transfer coefficient between the plate and the surrounding air, the unit is W / m 2 -K, value range 3~25W / m 2 -K, Tsurr is the temperature of the surrounding objects, T∞ is the temperature of the air, usually Tsurr = T∞, T6, T5, T4, T2, T8 are the temperatures of the components with corresponding numbers respectively, δ is the thickness of the plate, the unit is m.

[0078] The boundary center node is the node in the middle of the boundary of the entire PCB board, that is, the node of the second, fourth, sixth, and eighth components in the 3*3 electronic layout. Taking the sixth component as an example, the general expression of the node temperature obtained by the finite difference method is:

[0079]

[0080] Where q(2,3) refers to the heat generation rate per unit volume of the element in the second row and third column, that is, element No. 6, in W / m 3 .

[0081] The edge nodes are the nodes at the corners of the entire PCB board, that is, the nodes of the first, third, seventh and ninth components in the 3*3 electronic component layout. Taking the third component as an example, the general expression of the node temperature obtained by the finite difference method is:

[0082]

[0083] Where q(1,3) refers to the heat generation rate per unit volume of the element in the first row and third column, that is, element 3, in W / m 3 .

[0084] Step 120: Solve the temperature field according to a preset method and obtain the thermal layout of electronic components on the PCB board before and after optimization.

[0085] Specifically, MATLAB programming is used to solve the temperature field and obtain the thermal layout of electronic components on the PCB board before and after optimization.

[0086] Please refer to Figure 2 The method of using MATLAB programming to solve the temperature field and obtain the thermal layout of electronic components on the PCB before and after optimization includes:

[0087] The first step is the initialization process: at the beginning of the algorithm, the initial control parameter cont is set, the number of iterations iter = 100, and an initial solution x is randomly selected to generate, which is the starting solution of the entire algorithm iteration.

[0088] In the second step, under each initial control parameter cont, perform iter=1,2,3...100 times, and repeat the operations from the third to the sixth step in a loop;

[0089] The third step is to randomly generate a new solution x';

[0090] The fourth step is to calculate the difference between the evaluation function f(x) before and after, where the increment f = f(x') - f(x);

[0091] Step 5: If the increment f < 0, then the new solution x' is accepted with 100% probability and is taken as the current solution. Otherwise, the new solution is discarded or the new solution x' is accepted as the new current solution with a probability greater than a random number in (0, 1).

[0092] Step 6: If the algorithm meets the termination condition, the algorithm ends. The final current solution is the approximate optimal solution obtained by the simulated annealing algorithm, and the program is terminated at this time.

[0093] In the seventh step, cont gradually decreases, and cont>=0, then jumps to the second step.

[0094] As mentioned above, the solution space is the set and arrangement of all electronic components on the PCB. Taking a 3*3 electronic component layout as an example, the generated solution space output should be in the form of a 3*3 matrix, and the value of each position should change according to the solution space generated after each iteration. The value of each position represents the power of the component at that position; the purpose of the study is to find a component layout that makes the overall PCB board temperature the lowest, so the global maximum temperature Tmax when the electronic components on the PCB board are working is used as the objective function of this algorithm.

[0095] For example, the generation and acceptance rules for new solutions are described using nine components. The current solution is transformed using a two-transformation method to generate a new solution. Simply swapping any two components generates a new solution, such as x = {x1, x2, x3; x4, x5, x6; x7, x8, x9}. Randomly swapping x2 and x6 yields the following new solution: x' = {X1, X6, X3; X4, X5, X2; X7, X8, X9}. Whether a new solution is accepted is determined based on the Metropolis criterion of the simulated annealing algorithm. Solutions that are superior to the current solution are accepted directly, while solutions that are inferior are accepted with a certain probability. The Metropolis criterion is shown in Equation (4).

[0096]

[0097] If Ei < Ej, then accept j as the current state; otherwise, if the probability P = exp[-(Ei - Ej) / KT] is greater than a random number in the interval [0, 1), then still accept state j as the current state; if not, then retain state i as the current state. Here, E is the internal energy of a certain state at temperature T, Ei - Ej is its change amount, and K is the Boltzmann constant.

[0098] The flowchart for using MATLAB to solve the temperature field and obtain the thermal layout of electronic components on the PCB before and after optimization is as Figure 3 shown. First, randomly generate a layout. Using the general equation for the temperature difference of 9 components obtained in step 1, the temperature vector T = {T1, T2...T9} of the 9 components can be calculated by simple MATLAB programming; take the highest temperature among them as the highest temperature of the entire PCB board, and record the current layout as the optimal layout, and the current highest temperature Tpremax as the optimal temperature; then use the two-variable method to randomly generate another layout based on the current layout and calculate the temperature vector and the highest temperature Tmax under this layout. Determine whether Tmax is less than Tpremax. If it is less, then accept this layout as the optimal layout and Tmax as the optimal temperature; if not, then judge whether to accept this layout according to the Metropolis criterion; finally, judge whether the termination condition is reached. If not, then cool down and anneal and then iterate to calculate the optimal layout and the optimal temperature. If satisfied, then output the optimal layout and the optimal temperature; among them, cooling and annealing determine the accuracy of the entire algorithm, which is determined by the initial parameter cont and the attenuation factor. Generally, the attenuation factor is set between 0.90 - 0.99, and the initial value of the initial parameter cont is generally selected to be large enough. The number of internal Monte Carlo simulation iterations iter is set to 100.

[0099] Figures 5 to 7 is the result diagram of the temperature field vector of the 3*3 electronic component layout on the PCB obtained by MATLAB programming, as well as the result diagrams before and after layout optimization. The ambient temperature is set to 20°C, the thermal conductivity is set to λ = 0.3 W / M-K, and the default divided node grid is a square, that is: the horizontal and vertical coordinates of adjacent two components are equal, ΔX = ΔY = 1CM = 0.01M, ε is the emissivity of the flat plate, and its value is taken as 0.5,

[0100] where, σ is the Stefan - Boltzmann radiation constant, and its magnitude is 5.67×10 -8 W / m 2 -K 4 , h is the heat convection heat transfer coefficient between the flat plate and the surrounding air, with the unit of W / m 2 -K, and its value is 10 W / m 2-K, plate thickness δ = 3.4mm = 0.0034m; in the figure, S is the previous layout, T is the maximum temperature of the previous layout, S2 is the new layout generated based on S, T is the temperature vector under the S2 layout, Tpremax is the maximum temperature of the PCB board under the S2 layout, dC is the difference compared with the previous layout, since dC < 0, the S2 layout is accepted as the optimal layout, T = Tpremax is the optimal temperature, and the final optimal layout result is that S2 is the optimal layout under an ambient temperature of 20°C, and the value of Tpremax is the optimal temperature.

[0101] Step 130: Obtain the temperature cloud maps before and after the optimization according to a preset comparison rule, and compare the temperature cloud maps before and after the optimization.

[0102] Specifically, the three-dimensional thermal simulation software Icepak was used to perform simulations to obtain the temperature cloud maps before and after optimization, and the temperature cloud maps before and after optimization were compared.

[0103] The simulation using the three-dimensional thermal simulation software Icepak and the comparison of the results before and after optimization include:

[0104] Step 1301: Establish a corresponding thermal analysis model in Icepak, perform meshing in sequence, and check whether the meshing is correct;

[0105] Step 1302: If correct, set the boundary conditions of the model;

[0106] Step 1303 : Set the solution control parameters and solve the temperature field to obtain a temperature cloud map, and compare the conditions before and after the thermal layout optimization based on the temperature cloud map.

[0107] In order to further verify the accuracy of the results, it is necessary to use the three-dimensional thermal simulation software ICEPAK for simulation. The block module provided by ICEPAK is used to simulate electronic components. The size and spacing of the components are set according to the conditions in step 2. The final finite element three-dimensional simulation model is as follows: Figure 8 As shown, 1 is the PCB board model, 2 is the electronic component, and Q1, Q2...Q9 are the numbers of the 9 electronic components respectively.

[0108] Figure 9 This is a general calculation flow chart for thermal simulation, which mainly includes four parts: geometric model establishment, mesh division, calculation solution setting, and calculation result post-processing.

[0109] For example, the ambient temperature in the thermal simulation is set to 20 degrees Celsius, the air flow model is the turbulence model, the model calculation selects Realizable two equations, and the radiation heat transfer and gravity influence factors are turned on. According to the software setting requirements, the momentum relaxation factor is set to 0.7, the pressure relaxation factor is set to 0.3, the calculation accuracy is solved using single precision, the number of calculation iterations is 1000, the energy equation convergence residual is set to 0.001, and the flow equation convergence residual is set to 0.001. At the same time, a temperature monitoring point is set at the geometric center point of each chip surface. Finally, the temperature cloud map before layout optimization can be obtained ( Figure 10 ) and the temperature cloud map after layout optimization ( Figure 11 ). As for the global maximum temperature, it is lower after thermal layout optimization than before optimization, and thermal layout optimization increases heat dissipation.

[0110] As mentioned above, based on the existing component power, the finite difference method and simulated annealing algorithm are first used to obtain the layout of several components and calculate the highest temperature of the entire PCB board. Then, the simulated annealing algorithm is used to find the layout that makes the temperature of the entire PCB board the lowest. Finally, further verification is carried out through the three-dimensional thermal simulation software Icepak. The research method proposed in the present invention avoids the situation where the entire device malfunctions due to the high temperature of a component on the PCB board. In addition, the PCB temperature field obtained by the finite difference method takes into account the three situations of heat conduction, heat convection and heat radiation, and also avoids the temperature deviation that exists in actual applications. The optimal layout obtained can provide a certain theoretical basis for actual PCB plate making, avoid the possibility of high overall PCB temperature in blind plate making, and has high engineering research value.

[0111] The above are only preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that are possible for those skilled in the art will not depart from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include more other equivalent embodiments without departing from the concept of the present application. The scope of the present application is determined by the scope of the claims.

Claims

1. A method for optimizing and comparing the thermal layout of electronic components on a PCB, characterized in that: include: Calculate the general expression of the temperature of each electronic component on the PCB board according to the preset method; Solve the temperature field according to the preset method and obtain the thermal layout of electronic components on the PCB before and after optimization; Obtain the temperature cloud maps before and after optimization according to the preset comparison rules, and compare the temperature cloud maps before and after optimization; The general expression for calculating the temperature of each electronic component on the PCB board according to the preset method includes: Use the finite difference method to calculate the general expression for the temperature of each electronic component on the PCB board; The general expression for calculating the temperature of each electronic component on the PCB using the finite difference method includes: Set up a PCB area with a length of L, a width of λ, and a thickness of δ. Divide the area into M*N sub-areas, and the area nodes are (M+1)*(N+1). Get the temperature expression of the internal central node; Get the temperature expression of the boundary center node; Get the temperature expression of the edge node; The method of obtaining the temperature expression of the internal central node includes: Get the internal center node, which is the node on the component in the middle of the entire PCB board, that is, (M+1)*(N+1) / 2. The temperature expression of the internal center node is: Where λ is the thermal conductivity of the plate; q(k, l) is the heat generation rate per unit volume of the node in the kth row and lth column; ε is the emissivity of the plate; σ is the Stefan-Boltzmann radiation constant; h is the heat convection coefficient between the plate and the surrounding air; Tsurr is the temperature of the surrounding object; T∞ is the temperature of the air, and Tsurr = T∞; T k+1,l ,T k,l ,T k-1,l ,T k,l+1 ,T k,l-1 are the component temperatures in the corresponding rows and columns, respectively, and δ is the thickness of the plate.

2. The method for optimizing and comparing thermal layout of electronic components on a PCB according to claim 1, wherein: The temperature expression of the center node of the boundary is obtained, including: Get the boundary center node. The boundary center node is the node in the middle of the boundary of the entire PCB board, that is, the node of the even-numbered components in the M*N electronic layout. The expression of the boundary center node obtained by the finite difference method is: Here, q(i,j) refers to the heat generation rate per unit volume of the element in the i-th row and j-th column.

3. The method for optimizing and comparing thermal layout of electronic components on a PCB according to claim 1, wherein: The step of obtaining the temperature expression of the edge node includes: Obtain edge nodes. The edge nodes are nodes at the corner positions of the entire PCB board, that is, the nodes of the odd-numbered components in the M*N electronic component layout except the internal center node. The temperature expression of the edge nodes obtained by the finite difference method is: Where q(m,n) refers to the heat generation rate per unit volume of the element in the mth row and nth column.

4. The method for optimizing and comparing thermal layout of electronic components on a PCB according to claim 1, wherein: The method of solving the temperature field according to a preset method and obtaining the thermal layout of electronic components on the PCB before and after optimization includes: MATLAB programming is used to solve the temperature field and obtain the thermal layout of electronic components on the PCB board before and after optimization.

5. The method for optimizing and comparing thermal layout of electronic components on a PCB according to claim 4, wherein: The method of using MATLAB programming to solve the temperature field and obtain the thermal layout of electronic components on the PCB before and after optimization includes: The first step is the initialization process: at the beginning of the algorithm, the initial control parameter cont is set, the number of iterations iter = 100, and an initial solution x is randomly selected to generate the starting solution of the entire algorithm iteration; In the second step, under each initial control parameter cont, perform iter=1,2,3...100 times, and repeat the operations from the third to the sixth step in a loop; The third step is to randomly generate a new solution x'; The fourth step is to calculate the difference between the evaluation function f(x) before and after, where the increment f = f(x') - f(x); Step 5: If the increment f < 0, then the new solution x' is accepted with 100% probability and is taken as the current solution. Otherwise, the new solution is discarded or the new solution x' is accepted as the new current solution with a probability greater than a random number in (0, 1). Step 6: If the algorithm meets the termination condition, the algorithm ends. The final current solution is the approximate optimal solution obtained by the simulated annealing algorithm, and the program is terminated at this time. In the seventh step, cont gradually decreases, and cont>=0, then jumps to the second step.

6. The method for optimizing and comparing thermal layout of electronic components on a PCB according to claim 1, wherein: The step of obtaining the temperature cloud maps before and after optimization according to a preset comparison rule and comparing the temperature cloud maps before and after optimization includes: The three-dimensional thermal simulation software Icepak was used to perform simulations to obtain the temperature cloud maps before and after optimization, and the temperature cloud maps before and after optimization were compared.

7. The method for optimizing and comparing thermal layout of electronic components on a PCB according to claim 6, wherein: The simulation using the three-dimensional thermal simulation software Icepak and the comparison of the results before and after optimization include: Establish the corresponding thermal analysis model in Icepak, perform mesh division in sequence and check whether the mesh division is correct; If correct, set the boundary conditions of the model; The control parameters for the solution are set and the temperature field is solved to obtain a temperature cloud map, and the conditions before and after the thermal layout optimization are compared based on the temperature cloud map.

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