Vehicle-mounted equipment optimal configuration method and system, electronic equipment and storage medium

Abstract

The invention provides a vehicle-mounted equipment optimal configuration method and system, electronic equipment and a storage medium. The method comprises the steps that a finite element model, attribute configuration information and boundary condition configuration information of to-be-optimized vehicle-mounted equipment are acquired; according to the attribute configuration information and the boundary condition configuration information, simulating the finite element model to obtain a node temperature parameter of each target chip in the to-be-optimized vehicle-mounted equipment under the first to-be-optimized parameter and stress distribution information of the supporting component under the second to-be-optimized parameter; according to the node temperature parameter, optimizing the first to-be-optimized parameter to obtain a first optimized parameter, and according to the stress distribution information, optimizing the second to-be-optimized parameter to obtain a second optimized parameter; and optimizing and generating structure configuration information of the to-be-optimized vehicle-mounted equipment according to the first optimization parameter and the second optimization parameter. According to the invention, the efficiency and the accuracy of optimal configuration of the vehicle-mounted equipment are remarkably improved, so that the time and the labor cost of optimal configuration of the vehicle-mounted equipment are greatly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of product layout configuration, and in particular to a vehicle-mounted device optimization configuration method, system, electronic device and storage medium. Background Art

[0002] The optimal configuration of vehicle-mounted equipment is not only related to the performance and reliability of the vehicle-mounted equipment itself, but also directly affects the vehicle's fuel economy, driving safety, and passenger comfort. Therefore, how to optimize the configuration of vehicle-mounted equipment efficiently and accurately is an important issue that the industry needs to solve urgently.

[0003] The configuration of existing vehicle-mounted equipment mainly relies on the experience of designers and historical checklists for design and implementation. It is difficult to efficiently and accurately design an optimal configuration plan for vehicle-mounted equipment, which leads to the need for repeated design improvements and verification test retests when problems arise in subsequent verification tests, thereby increasing the time and labor costs for optimizing the configuration of vehicle-mounted equipment.

[0004] Therefore, there is an urgent need to provide a method, system, electronic device and storage medium for optimizing configuration of vehicle-mounted equipment. Summary of the invention

[0005] The present invention provides a method, system, electronic device and storage medium for optimizing the configuration of vehicle-mounted equipment, which are used to solve the defect in the prior art that the design of vehicle-mounted equipment relies on the experience of designers and historically accumulated checklists, resulting in high time and labor costs for optimizing the configuration of vehicle-mounted equipment, and significantly improve the efficiency and accuracy of optimizing the configuration of vehicle-mounted equipment, thereby greatly reducing the time and labor costs for optimizing the configuration of vehicle-mounted equipment.

[0006] The present invention provides a method for optimizing configuration of vehicle-mounted equipment, comprising: Obtaining the finite element model, attribute configuration information and boundary condition configuration information of the vehicle-mounted equipment to be optimized; According to the attribute configuration information and the boundary condition configuration information, the finite element model is simulated to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized; According to the node temperature parameter, the first parameter to be optimized is optimized to obtain a first optimized parameter, and according to the stress distribution information, the second parameter to be optimized is optimized to obtain a second optimized parameter; Optimizing and generating structural configuration information of the vehicle-mounted device to be optimized according to the first optimization parameter and the second optimization parameter; The first parameter to be optimized is a structural parameter to be optimized of a heat dissipation component in the vehicle-mounted device to be optimized, and the second parameter to be optimized is a structural parameter to be optimized of the supporting component.

[0007] According to a vehicle-mounted device optimization configuration method provided by the present invention, the first parameter to be optimized is optimized according to the node temperature parameter to obtain the first optimized parameter, including: In the attribute configuration information, searching for the maximum operating temperature parameter of each of the target chips; Constructing a target cost function according to the node temperature parameter, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized; The first parameter to be optimized is optimized according to the target cost function to obtain the first optimized parameter.

[0008] According to a vehicle-mounted device optimization configuration method provided by the present invention, the target cost function is constructed according to the node temperature parameter, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized, including: Taking the node temperature parameter of each target chip as less than or equal to the maximum operating temperature parameter of each target chip as a target, constructing a first cost function; A second cost function is constructed with the goal of minimizing the weighted sum of the node temperature parameters of all the target chips; Constructing a third cost function with the goal of minimizing the size cost corresponding to the first parameter to be optimized; The target cost function is constructed by combining the first cost function, the second cost function and the third cost function.

[0009] According to a vehicle-mounted device optimization configuration method provided by the present invention, after optimizing the first parameter to be optimized according to the node temperature parameter to obtain the first optimized parameter, the method further includes: updating the finite element model according to the first optimization parameter to obtain an updated finite element model; Performing a temperature rise test on a vehicle-mounted device prototype corresponding to the first optimization parameter to obtain a first node temperature parameter of each target chip under the first optimization parameter; Performing a temperature rise test on the updated finite element model to obtain a second node temperature parameter of each target chip under the first optimization parameter; A regression analysis is performed on the error between the first node temperature parameter and the second node temperature parameter, and the attribute configuration information is updated according to the regression analysis result.

[0010] According to a vehicle-mounted equipment optimization configuration method provided by the present invention, the second parameter to be optimized is optimized according to the stress distribution information to obtain the second optimized parameter, including: Obtaining stress parameters of different stress-bearing parts of the support component at different positions from the stress distribution information; Among the multiple stress-bearing parts of the support component, locate a first stress-bearing part having a stress parameter greater than a preset stress parameter; In the second parameter to be optimized, a first sub-parameter corresponding to the first stress-bearing part is obtained, and the first sub-parameter is optimized with the goal of optimizing the stress parameters of the first stress-bearing part in different directions to be less than or equal to the preset stress parameters; Determining the second optimized parameter according to the optimized first sub-parameter; Wherein, the preset stress parameter is determined according to the fatigue strength of the supporting component.

[0011] According to a vehicle-mounted device optimization configuration method provided by the present invention, determining the second optimization parameter according to the optimized first sub-parameter includes: Among the multiple stress-bearing parts of the support component, locate a second stress-bearing part having a stress parameter less than or equal to the preset stress parameter; In the second parameter to be optimized, a second sub-parameter corresponding to the second stress-bearing part is obtained, and the second sub-parameter is optimized with the goal that the stress parameter of the second stress-bearing part in different directions is less than or equal to the preset stress parameter and the mass of the supporting component is minimized; The second optimized parameter is determined according to the optimized second sub-parameter and the optimized first sub-parameter.

[0012] According to a vehicle-mounted equipment optimization configuration method provided by the present invention, the first sub-parameter includes at least one of a thickness configuration parameter, a mounting foot height configuration parameter, a flange height configuration parameter, a chamfer radius configuration parameter, a crack stop groove configuration parameter, a strength configuration parameter, and a rib position configuration parameter; The second sub-parameters include structural lightweight configuration parameters and / or density configuration parameters.

[0013] According to a vehicle-mounted device optimization configuration method provided by the present invention, the finite element model is simulated according to the attribute configuration information and the boundary condition configuration information to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the support component in the vehicle-mounted device to be optimized under the second parameter to be optimized, including: In the attribute configuration information, searching for the first configuration information and the second configuration information of the vehicle-mounted device to be optimized; In the boundary condition configuration information, searching for the temperature boundary condition, displacement boundary condition and load boundary condition of the vehicle-mounted equipment to be optimized; Simulating the finite element model according to the first configuration information and the temperature boundary condition to obtain the node temperature parameters of each of the target chips under the first parameters to be optimized; Simulating the finite element model according to the second configuration information, the displacement boundary condition and the load boundary condition to obtain stress distribution information of the support component under the second parameter to be optimized; Wherein, the first configuration information includes material model, thermal conductivity information and thermal performance information, and the second configuration information includes material model and material mechanical property information; The temperature boundary conditions include boundary conditions for constraining the ambient temperature of the vehicle-mounted equipment to be optimized; the displacement boundary conditions include boundary conditions for constraining the installation position of the vehicle-mounted equipment to be optimized; and the load boundary conditions include boundary conditions for constraining the power spectral density distribution information of the vehicle-mounted equipment to be optimized.

[0014] The present invention also provides a vehicle-mounted equipment optimization configuration system, comprising: An acquisition unit, used to acquire a finite element model, attribute configuration information, and boundary condition configuration information of the vehicle-mounted equipment to be optimized; A simulation unit, configured to simulate the finite element model according to the attribute configuration information and the boundary condition configuration information, to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized; A first optimization unit is used to optimize the first parameter to be optimized according to the node temperature parameter to obtain a first optimized parameter, and optimize the second parameter to be optimized according to the stress distribution information to obtain a second optimized parameter; A second optimization unit, configured to optimize and generate the structural configuration information of the vehicle-mounted device to be optimized according to the first optimization parameter and the second optimization parameter; The first parameter to be optimized is a structural parameter to be optimized of a heat dissipation component in the vehicle-mounted device to be optimized, and the second parameter to be optimized is a structural parameter to be optimized of the supporting component.

[0015] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the above-mentioned vehicle-mounted equipment optimization configuration methods is implemented.

[0016] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the vehicle-mounted equipment optimization configuration method described in any one of the above is implemented.

[0017] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned vehicle-mounted device optimization configuration methods.

[0018] The vehicle-mounted equipment optimization configuration method, system, electronic device and storage medium provided by the present invention obtain the finite element model of the vehicle-mounted equipment to be optimized and its attribute configuration information and boundary condition configuration information; and refine and automatically simulate the finite element model based on these configuration information to obtain the node temperature parameters of the target chip under the structural parameters to be optimized of the heat dissipation component, and the stress distribution information of the supporting component under its structural parameters to be optimized; optimize the first parameter to be optimized based on the node temperature parameter to obtain the first optimization parameter, and optimize the second parameter to be optimized based on the stress distribution information to obtain the second optimization parameter; finally, based on these optimization parameters, optimize and generate the structural configuration information of the vehicle-mounted equipment to be optimized, thereby combining the finite element model, design experience and automated simulation process to intelligently optimize the two key design areas of heat dissipation and strength of the vehicle-mounted equipment, which not only significantly improves the efficiency and accuracy of the vehicle-mounted equipment optimization configuration, but also ensures the one-time pass rate of the DV test, thereby reducing the problems that may arise in subsequent verification tests and the required design improvements and verification test retest times, thereby greatly reducing the time and labor costs of optimizing the configuration of the vehicle-mounted equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a flow chart of the vehicle-mounted equipment optimization configuration method provided by the present invention.

[0021] Figure 2 It is a structural schematic diagram of the geometric model of the vehicle-mounted equipment to be optimized provided by the present invention.

[0022] Figure 3 It is a structural schematic diagram of the grid model provided by the present invention.

[0023] Figure 4 It is a schematic diagram of a process for optimizing the first parameter to be optimized provided by the present invention.

[0024] Figure 5 This is one of the structural schematic diagrams of the heat dissipation fins of the upper cover provided by the present invention.

[0025] Figure 6 This is the second structural schematic diagram of the heat dissipation fins of the upper cover provided by the present invention.

[0026] Figure 7 It is a simulation schematic diagram of a DOE example corresponding to the first parameter to be optimized provided by the present invention.

[0027] Figure 8 It is a simulation schematic diagram of the thermal simulation verification based on the modified property configuration information provided by the present invention.

[0028] Fig. 9 This is one of the structural schematic diagrams of the supporting component provided by the present invention.

[0029] Fig.10 The weight of the X-axis support component provided by the present invention and the weight of the force point Schematic diagram of stress value distribution.

[0030] Fig.11 The weight of the Y-axis support component provided by the present invention and the weight of the force point Schematic diagram of stress value distribution.

[0031] Fig.12 The weight of the Z-axis support component provided by the present invention and the weight of the force point Schematic diagram of stress value distribution.

[0032] Fig.13 The thickness of the support component of the X-axis provided by the present invention and the 1st of the force point Schematic diagram of stress value distribution.

[0033] Fig.14 The thickness of the support component of the Y axis provided by the present invention and the stress point are Schematic diagram of stress value distribution.

[0034] Fig.15 The thickness of the support component of the Z axis provided by the present invention is 1 Schematic diagram of stress value distribution.

[0035] Fig.16 This is the second structural schematic diagram of the supporting component provided by the present invention.

[0036] Fig.17 This is the third structural schematic diagram of the supporting component provided by the present invention.

[0037] Fig.18 The height of the mounting foot of the X-axis support component provided by the present invention is 1 Schematic diagram of stress value distribution.

[0038] Fig.19 The height of the mounting foot of the Y-axis support component provided by the present invention is 1 Schematic diagram of stress value distribution.

[0039] Fig. 20 The height of the mounting foot of the Z-axis support component provided by the present invention is 1 Schematic diagram of stress value distribution.

[0040] Fig.21 This is the fourth structural schematic diagram of the supporting component provided by the present invention.

[0041] Fig. 22 It is a structural schematic diagram of the vehicle-mounted equipment optimization configuration system provided by the present invention.

[0042] Fig.23 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] The existing design method of vehicle-mounted equipment (also called vehicle-mounted products) is mainly based on the experience of the previous design of the upper cover and mounting bracket of the vehicle-mounted equipment and the accumulated checklist (also called checklist). However, it is difficult to fully evaluate the risks of heat dissipation and mechanical strength in the early design through empirical design alone, and it is difficult to efficiently and accurately design the optimal configuration of the vehicle-mounted equipment. As a result, a lot of design improvements and test retesting time and cost are required after problems occur in the subsequent design verification (DV) test, thereby increasing the time and labor cost of optimizing the configuration of vehicle-mounted equipment.

[0045] In this regard, in view of the problem that the prior art fails to evaluate and avoid the risks of heat dissipation and mechanical strength of vehicle-mounted products through simulation, resulting in insufficient reliability design of vehicle-mounted equipment and increased time and labor costs for optimizing configuration of vehicle-mounted equipment, the present application provides a method for optimizing configuration of vehicle-mounted equipment. By combining finite element models, design experience and automated simulation processes, the two key design areas of heat dissipation and strength of vehicle-mounted products are optimized. This not only improves the reliability, accuracy and portability of the optimized configuration of the vehicle-mounted equipment, but also ensures the one-time pass rate of the DV test, thereby effectively reducing the time and labor costs for optimizing configuration of the vehicle-mounted equipment.

[0046] Figure 1 The figure is a flow chart of the vehicle-mounted device optimization configuration method provided by the present invention. The method can effectively improve the reliability of the vehicle-mounted device by optimizing the structural parameters of the vehicle-mounted device.

[0047] It should be noted that the execution subject of the method can be a vehicle-mounted equipment optimization configuration system, which can perform various functions such as parameter configuration, model construction, model simulation, verification, and parameter optimization configuration, which can assist in realizing the optimization configuration of vehicle-mounted equipment. The system can be an electronic device, a controller, or a simulation system, etc., which is not specifically limited in this embodiment. Among them, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a wearable device, a super mobile personal computer, etc., and the non-mobile electronic device can be a server, a network attached storage, a personal computer, etc., which is not specifically limited in the present invention.

[0048] like Figure 1 As shown, the method includes step 110 , step 120 , step 130 and step 140 .

[0049] Step 110: Obtain the finite element model, attribute configuration information, and boundary condition configuration information of the vehicle-mounted equipment to be optimized.

[0050] Optionally, when performing the optimization configuration of the vehicle-mounted equipment to be optimized, it is necessary to obtain in advance the finite element model, attribute configuration information and boundary condition configuration information of the vehicle-mounted equipment to be optimized.

[0051] Here, the vehicle-mounted equipment to be optimized here can be the vehicle-mounted equipment that needs to be optimized, such as a vehicle-mounted controller, etc., and this embodiment does not specifically limit this. The finite element model of the vehicle-mounted equipment to be optimized refers to a digital model established when the vehicle-mounted equipment to be optimized is simulated and analyzed using the finite element analysis method. The model is used to simulate the working behavior of the vehicle-mounted equipment under actual working conditions.

[0052] The steps for obtaining the finite element model of the vehicle equipment to be optimized specifically include: A geometric model of the vehicle-mounted equipment to be optimized, such as a three-dimensional (also called 3D) model, is established. The geometric model of the vehicle-mounted equipment includes multiple components, as well as the connection relationship and shape between the components.

[0053] Figure 2 is a schematic diagram of the structure of the geometric model of the vehicle-mounted equipment to be optimized provided by the present invention; Figure 2 As shown, the components in the geometric model here include but are not limited to an upper cover, a printed circuit board (PCB), a bottom shell and a supporting component; wherein the upper cover is provided with a heat dissipation component, such as a heat dissipation fin, which is a key area for the heat dissipation design of the whole machine; the supporting component, which may be a bracket provided with a bracket mounting foot, is a key area for the mechanical strength design of the whole machine, and the remaining structural parts, such as the bottom shell, mainly play an enveloping and protective role for the PCB of the vehicle-mounted equipment.

[0054] The method provided in this embodiment is described below by taking the supporting component as a bracket and the heat dissipating component as a heat dissipating fin as an example.

[0055] After the geometric model of the vehicle-mounted equipment is constructed, the vehicle-mounted product geometric model can be imported into a finite element simulation model to establish a finite element model of the vehicle-mounted equipment to be optimized.

[0056] Here, the attribute configuration information includes but is not limited to material model, thermal conductivity information and thermal performance information, and material mechanical property information, which is not specifically limited in this embodiment. The attribute configuration information can be user input entered by the user in the front-end interface according to the optimization configuration requirements of the vehicle-mounted equipment to be optimized, or it can be loaded and obtained from the configuration information pre-stored in the system according to the optimization configuration requirements of the vehicle-mounted equipment to be optimized. This embodiment does not make specific limitations on this. The so-called user input can be information input through a command line interface, a graphical interface, touch input, a drop-down selection input, voice input, etc. This embodiment does not make specific limitations on this.

[0057] Here, the boundary condition configuration information includes multiple boundary conditions set according to the optimization configuration requirements and / or working condition information. These boundary conditions are constraints imposed on the boundary or contact surface of the finite element model, and are used to limit the degree of freedom of the structure of the vehicle-mounted equipment simulation model in the finite element model. The boundary condition configuration information includes multiple items of displacement boundary conditions, load boundary conditions, and temperature boundary conditions.

[0058] Step 120, simulating the finite element model according to the attribute configuration information and the boundary condition configuration information, to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized; wherein, the first parameter to be optimized is the structural parameter to be optimized of the heat dissipation component in the vehicle-mounted device to be optimized, and the second parameter to be optimized is the structural parameter to be optimized of the supporting component.

[0059] Figure 3 It is a structural schematic diagram of the grid model provided by the present invention.

[0060] Optionally, after obtaining the finite element model, attribute configuration information, and boundary condition configuration information of the vehicle-mounted equipment to be optimized, the finite element model may be meshed to obtain mesh models of each component; for example, the model may be meshed according to a certain aspect ratio value, where the aspect ratio value may be set according to actual needs, such as being set to within 20 to ensure the overall quality of the mesh and the accuracy of the finite element analysis. The specific meshing results are as follows: Figure 3 As shown. For another example, the finite element model can be meshed according to the structural characteristics of the vehicle-mounted equipment to be optimized and the requirements of simulation analysis. For example, in the finite element model, the bottom shell and the bracket are divided into quadrilateral shell elements (also called S4R), the upper cover is divided into second-order tetrahedral elements (also called C3D10M); the PCB board is mainly divided into hexahedral elements (also called C3D8R), etc., so as to better simulate the structural characteristics of each component in the vehicle-mounted equipment to be optimized of this structure.

[0061] After obtaining the mesh models of each component, the corresponding attribute configuration information and boundary condition configuration information can be applied to the mesh models of each component to configure the finite element model. After the configuration is completed, the finite element thermal simulation software in the finite element analysis software can be called to perform thermal simulation on the finite element model according to the configuration information related to thermal simulation to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized; and the finite element mechanical simulation software in the finite element analysis software can be called to perform mechanical simulation on the finite element model according to the configuration information related to mechanical simulation to obtain the stress distribution information of the supporting components in the vehicle-mounted device to be optimized under the second parameter to be optimized. The target chip here can be a key chip that can generate a heat source.

[0062] The first parameter to be optimized is the structural parameter to be optimized of the heat dissipation component in the vehicle-mounted device to be optimized, that is, the key parameter that affects the temperature change of each component in the vehicle-mounted device to be optimized, including but not limited to at least one of the height, thickness, and spacing of the heat dissipation component. The second parameter to be optimized is the structural parameter to be optimized of the support component in the vehicle-mounted device to be optimized, that is, the key parameter that affects the load-bearing performance of the vehicle-mounted device to be optimized, including but not limited to at least one of the thickness configuration parameters, density configuration parameters, mounting foot height configuration parameters, flange height configuration parameters, chamfer radius configuration parameters, crack stop groove configuration parameters, strength configuration parameters, rib position configuration parameters, and structural lightweight configuration parameters.

[0063] Step 130: optimizing the first parameter to be optimized according to the node temperature parameter to obtain a first optimized parameter, and optimizing the second parameter to be optimized according to the stress distribution information to obtain a second optimized parameter.

[0064] Optionally, after simulating and obtaining the node temperature parameters of each target chip under the first parameters to be optimized, the optimization module designed based on finite element thermal simulation can be used to apply the node temperature parameters of each target chip under the first parameters to be optimized to determine the cost function, and based on the cost function, the first parameters to be optimized are iteratively optimized until the optimization goal is reached (such as the minimum cost function), then the optimization step of the first parameters to be optimized is stopped, and the optimized first parameters to be optimized that meet the optimization goal are used as the optimized structural parameters of the heat dissipation components in the vehicle-mounted equipment to be optimized, that is, the first optimized parameters.

[0065] Similarly, after simulating and obtaining the stress distribution information of the supporting component under the second parameter to be optimized, the optimization module of the finite element mechanical simulation design can be used to apply the stress distribution information of the supporting component under the second parameter to be optimized to determine the cost function, and based on the cost function, the second parameter to be optimized is iteratively optimized until the optimization target is reached. The optimization step of the second parameter to be optimized is stopped, and the optimized second parameter to be optimized that meets the optimization target is used as the optimized structural parameter of the supporting component in the vehicle-mounted equipment to be optimized, that is, the second optimization parameter.

[0066] Step 140: Optimize and generate the structural configuration information of the vehicle-mounted device to be optimized according to the first optimization parameter and the second optimization parameter.

[0067] Optionally, after obtaining the first optimization parameter and the second optimization parameter, the original structural configuration information of the vehicle-mounted equipment to be optimized is optimized after integrating the first optimization parameter and the second optimization parameter to generate the final structural configuration information of the vehicle-mounted equipment to be optimized, so that the vehicle-mounted equipment to be optimized can be subsequently optimized based on the structural configuration information of the vehicle-mounted equipment to be optimized generated by optimization, so that the physical vehicle-mounted equipment optimized thereby has higher reliability.

[0068] The method provided in this embodiment obtains the finite element model of the vehicle-mounted equipment to be optimized and its attribute configuration information and boundary condition configuration information; and refines and automatically simulates the finite element model based on these configuration information to obtain the node temperature parameters of the target chip under the structural parameters to be optimized of the heat dissipation component, and the stress distribution information of the supporting component under its structural parameters to be optimized; optimizes the first parameter to be optimized based on the node temperature parameter to obtain the first optimized parameter, and optimizes the second parameter to be optimized based on the stress distribution information to obtain the second optimized parameter; finally, based on these optimized parameters, optimizes and generates the structural configuration information of the vehicle-mounted equipment to be optimized, thereby combining the finite element model, design experience and automated simulation process to intelligently optimize the two key design areas of heat dissipation and strength of the vehicle-mounted equipment, which not only significantly improves the efficiency and accuracy of the optimized configuration of the vehicle-mounted equipment, but also ensures the one-time pass rate of the DV test, thereby reducing the problems that may arise in subsequent verification tests and the required number of design improvements and verification test retests, thereby greatly reducing the time and labor costs for the optimized configuration of the vehicle-mounted equipment.

[0069] In some embodiments, step 130 specifically includes: searching for the maximum operating temperature parameter of each target chip in the attribute configuration information; constructing a target cost function according to the node temperature parameter, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized; optimizing the first parameter to be optimized according to the target cost function to obtain the first optimized parameter.

[0070] Figure 4 is a flow chart of parameter optimization of the first parameter to be optimized provided by the present invention; Figure 4 As shown, when optimizing the first parameter to be optimized, the optimization module of finite element thermal simulation design is used, the Design of Experiments (DOE) example is input, the first parameter to be optimized is defined as the input parameter, the node temperature parameter of each target chip is defined as the output parameter, and the target cost function constructed based on the node temperature parameter, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized is defined as the cost function, and the parameter optimization is solved after setting the DOE example, and a response surface is generated based on the solution results. The optimal solution (that is, the solution corresponding to the minimum value of the cost function) and the corresponding recommended values ​​of the input parameters can be obtained from the response surface, thereby obtaining the first optimized parameter.

[0071] The following describes the optimization steps of the first parameter to be optimized with a specific example.

[0072] Figure 5 This is one of the structural schematic diagrams of the heat dissipation fins of the upper cover provided by the present invention; Figure 6FIG. 2 is a second structural diagram of the heat dissipation fins of the upper cover provided by the present invention. For example, Figure 5 and Figure 6 As shown, the height and spacing of the heat dissipation fins of the upper cover can be used as the first parameters to be optimized, that is, input parameters.

[0073] The node temperature parameters of the plurality of target chips are used as output parameters, and a target cost function constructed by using the node temperature parameters, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized is used as a cost function.

[0074] For each sub-parameter in the first parameter to be optimized, multiple DOE examples are set, such as at least 10 DOE examples. For example, 20 DOE examples can be set for the two input parameters of the height and spacing of the heat dissipation fins of the upper cover, as shown in Table 1.

[0075] Table 1 Data table of the DOE example corresponding to the first parameter to be optimized After the DOE example is set up, the optimization module of the finite element thermal simulation design is used to simulate and solve the DOE example corresponding to each sub-parameter in the first parameter to be optimized, so as to directly generate the DOE example corresponding to the optimal solution that minimizes the target cost function as the first optimization parameter, or generate a response surface based on the simulation solution results, and obtain the DOE example corresponding to the optimal solution that minimizes the target cost function from the response surface as the first optimization parameter.

[0076] Figure 7 is a simulation schematic diagram of a DOE example corresponding to the first parameter to be optimized provided by the present invention; Figure 7 As shown, the input parameters corresponding to the optimal solution with the lowest cost function are the fin height of 40 mm and the fin spacing of 9.3 mm. Therefore, it can be used as the first optimization parameter for the final optimization.

[0077] The method provided in this embodiment optimizes the structural parameters of the heat dissipation components by finding the maximum operating temperature parameters of the target chip and constructing a target cost function in combination with the node temperature, the maximum operating temperature and the size cost of the parameters to be optimized, thereby achieving a lean design of the heat dissipation components while ensuring the heat dissipation safety of the components, thereby reducing the weight of the upper cover and the production cost.

[0078] In some embodiments, the step of obtaining the target cost function specifically includes: constructing a first cost function with the goal that the node temperature parameter of each target chip is less than or equal to the maximum operating temperature parameter of each target chip; constructing a second cost function with the goal of minimizing the weighted addition result between the node temperature parameters of all the target chips; constructing a third cost function with the goal of minimizing the size cost corresponding to the first parameter to be optimized; and constructing the target cost function by combining the first cost function, the second cost function and the third cost function.

[0079] Optionally, during the thermal simulation solution process, a first cost function is constructed with the goal of ensuring that the node temperature parameters of each target chip are less than or equal to the maximum operating temperature parameters of each target chip, thereby ensuring that the first optimization parameters obtained by the solution can ensure that the node temperature parameters of each target chip are less than or equal to the maximum operating temperature parameters of each target chip, thereby ensuring the safety of the optimized design of the vehicle-mounted equipment.

[0080] In addition, the node temperature parameters of all target chips are weighted and summed, and a second cost function is constructed with the goal of minimizing the weighted sum of the node temperature parameters of all target chips, thereby ensuring the optimization of the overall heat dissipation performance while reducing the risk caused by local overheating.

[0081] Exemplarily, assuming that the junction temperature parameters of the plurality of target chips are T0, T1, and T2, respectively, the weighted summation result is S2=T0×w0+T1×w1+T2×w2, where w0, w1, and w2 are weight coefficients.

[0082] In addition, the corresponding dimensional cost can be calculated based on the dimensional parameters in the first parameter to be optimized, and a third cost function can be constructed with the goal of minimizing the dimensional cost corresponding to the first parameter to be optimized to ensure the lean design of the heat dissipation components and reduce the weight and production cost of the upper cover.

[0083] For example, the height H and the spacing S of the fins in the first parameter to be optimized are multiplied to obtain the size cost corresponding to the first parameter to be optimized.

[0084] After obtaining the first cost function, the second cost function and the third cost function, they can be weightedly added to obtain a target cost function that realizes lean design of heat dissipation components while ensuring heat dissipation safety of components and reduces the weight of the upper cover and production costs.

[0085] The method provided in this embodiment constructs a comprehensive target cost function by jointly considering the chip operating temperature limit, overall heat dissipation performance optimization and cost-effectiveness, thereby achieving multi-dimensional optimization of the heat dissipation system design and ensuring efficient and stable operation and cost savings of the vehicle-mounted equipment in a high temperature environment.

[0086] In some embodiments, after executing step 130, the following steps may also be executed: updating the finite element model according to the first optimization parameter to obtain an updated finite element model; performing a temperature rise test on the vehicle-mounted equipment prototype corresponding to the first optimization parameter to obtain the first node temperature parameters of each target chip under the first optimization parameter; performing a temperature rise test on the updated finite element model to obtain the second node temperature parameters of each target chip under the first optimization parameter; performing a regression analysis on the error between the first node temperature parameter and the second node temperature parameter, and updating the attribute configuration information based on the regression analysis result.

[0087] Optionally, after obtaining the first optimization parameter, the geometric model of the vehicle-mounted device to be optimized can be optimized based on the first optimization parameter, thereby updating and constructing the finite element model based on the optimized geometric model to generate an updated finite element model. In addition, a prototype can be made for the first optimization parameter to obtain a prototype of the vehicle-mounted device corresponding to the first optimization parameter.

[0088] Table 2 Data distribution table of thermal simulation database In some embodiments, step 130 further includes: obtaining stress parameters of different stress-bearing parts of the support component in different directions from the stress distribution information; locating a first stress-bearing part having a stress parameter greater than a preset stress parameter among multiple stress-bearing parts of the support component; obtaining a first sub-parameter corresponding to the first stress-bearing part in the second parameter to be optimized, and optimizing the first sub-parameter with the goal of optimizing the stress parameter of the first stress-bearing part in different directions to be less than or equal to the preset stress parameter; determining the second optimized parameter based on the optimized first sub-parameter; wherein the preset stress parameter is determined based on the fatigue strength of the support component.

[0089] Optionally, when optimizing the second parameter to be optimized, the stress parameters of different stress-bearing parts of the support component in different directions can be firstly obtained by analyzing the stress distribution information. The stress parameters here can be the stress parameters of different stress-bearing parts of the support component in different directions, excluding the stress singularity at the screw point. Stress value (such as the maximum 1 at the mounting foot of the bracket stress value, etc.) by 3, and the obtained stress values ​​of different support parts in different directions are 3 Stress value.

[0090] Here, 1 The stress value may include the mechanical simulation of the finite element model according to the attribute configuration information and the boundary condition configuration information, and the different stress-bearing parts of the support component are simulated and solved in the three loading directions of the X axis, the Y axis, and the Z axis. Stress value.

[0091] Then, 3 The stress value is compared with the preset stress parameter corresponding to the fatigue strength of the supporting component to determine whether there is a stress-bearing part with a positioning stress parameter greater than the preset stress parameter among the multiple stress-bearing parts of the supporting component. If there is, it is determined that the stress of the stress-bearing part is large and there is a risk of fatigue failure, and it is taken as the first stress-bearing part. The first stress-bearing part with large stress is structurally optimized to reduce its 3 The stress value makes the first stress-bearing part in different directions 3 The stress value is optimized to be less than or equal to the preset stress parameter corresponding to the fatigue strength of the supporting component, thereby eliminating the risk of fatigue failure of this part. The specific implementation steps are as follows: In the second parameter to be optimized, the first sub-parameter influencing the fatigue failure risk in the first stress-bearing part is obtained to optimize the first stress-bearing part in different directions. The stress value is optimized to be less than or equal to the preset stress parameter corresponding to the fatigue strength of the supporting component, and the first sub-parameter is iteratively optimized until the optimization obtains 3 stress values ​​that can make the first stress-bearing part in different directions The stress value is optimized to be less than or equal to the optimized first sub-parameter of the preset stress parameter corresponding to the fatigue strength of the supporting component, and the second optimized parameter is determined based on the optimized first sub-parameter.

[0092] In some embodiments, the first sub-parameter includes at least one of a thickness configuration parameter, a mounting foot height configuration parameter, a flange height configuration parameter, a chamfer radius configuration parameter, a crack stop groove configuration parameter, a strength configuration parameter, and a rib position configuration parameter.

[0093] Among them, the thickness configuration parameter is used to optimize the thickness of the bracket, such as appropriately increasing the thickness of the bracket (such as the auxiliary bracket) to improve the structural strength. The mounting foot height configuration parameter is used to optimize the height of the mounting foot of the bracket to improve the structural strength. The flange height configuration parameter is used to optimize the flange height, such as appropriately increasing the flange height to improve the structural strength. The chamfer radius configuration parameter is used to optimize the chamfer radius, such as appropriately increasing the chamfer radius to improve the structural strength. The crack stop groove configuration parameter is used to optimize the location of the crack stop groove, such as opening a crack stop groove-like structure at a stress concentration location to improve stress distribution. The strength configuration parameter is used to optimize the strength of the material, such as replacing a higher strength material to improve the structural strength. The rib position configuration parameter is used to optimize the number of rib positions, such as reducing the number of rib positions to reduce costs.

[0094] Through the first sub-parameter determined above, the structural design can be optimized for the location with greater stress to effectively reduce 3 Stress value, thereby eliminating the risk of fatigue failure at each stress-bearing part and improving the design reliability of the bracket.

[0095] In some embodiments, determining the second optimized parameter based on the optimized first sub-parameter includes: locating a second stress-bearing part having a stress parameter less than or equal to the preset stress parameter among the multiple stress-bearing parts of the support component; obtaining a second sub-parameter corresponding to the second stress-bearing part among the second parameters to be optimized, and optimizing the second sub-parameter with the goal that the stress parameter of the second stress-bearing part in different orientations is less than or equal to the preset stress parameter and the mass of the support component is minimized; determining the second optimized parameter based on the optimized second sub-parameter and the optimized first sub-parameter.

[0096] Optionally, in the 3 By comparing the stress value with the preset stress parameter corresponding to the fatigue strength of the support component, it can also be determined whether there is a stress-bearing part with a positioning stress parameter less than or equal to the preset stress parameter among the multiple stress-bearing parts of the support component. If so, it is determined that the stress of the stress-bearing part is small and there is no risk of fatigue failure. However, in order to further lightweight the support component, it can be used as the second stress-bearing part to perform material lightweight processing on the second stress-bearing part, reduce the weight of the support component, and improve the reliability of the support component. The specific implementation steps are as follows: Among the second parameters to be optimized, a second sub-parameter in the second stress-bearing part that affects the weight of the supporting component is obtained, and the second sub-parameter is iteratively optimized with the goal of optimizing the material mass of the second stress-bearing part to the minimum on the premise that the stress parameters of the second stress-bearing part in different orientations are less than or equal to the preset stress parameters. The second sub-parameter is obtained by optimization until the optimized second sub-parameter is obtained in which the material mass of the second stress-bearing part is minimized on the premise that the stress parameters of the second stress-bearing part in different orientations are less than or equal to the preset stress parameters. The second optimized parameter is then determined by combining the optimized first sub-parameter and the optimized second sub-parameter.

[0097] In some embodiments, the second sub-parameter includes a structural lightweight configuration parameter and / or a density configuration parameter.

[0098] Among them, the structural lightweight configuration parameters are used to lightweight some materials, such as hollowing out the middle part of the support component, that is, removing some materials from the middle part of the support component. The density configuration parameters are used to optimize the material density, such as selecting a lighter material. Therefore, through the above second sub-parameters, the structural lightweight design optimization can be performed for places with less stress, so as to ensure that there is no risk of fatigue failure in each stress-bearing part, reduce the weight of the bracket, and improve the design reliability of the support component.

[0099] The following is a specific example to verify the effect of optimizing the second parameter to be optimized on improving the reliability of the supporting component.

[0100] For the supporting components, multiple instances corresponding to the second parameters to be optimized are set, such as the thickness of the bracket is set in four combinations of 1.5mm, 1.8mm, 2.0mm, and 2.5mm, the height of the mounting feet is set in five combinations of H=5mm, 15mm, 25mm, 35mm, and 50mm, and the weight of the bracket body is adjusted by adjusting the density of the body, setting the weight in five combinations of W=50%, 75%, 100%, 125%, and 150%, etc., and parametric analysis and verification are performed through the above mechanical simulation steps.

[0101] Fig. 9 is one of the structural schematic diagrams of the support component provided by the present invention; Fig. 9 As shown, four stress points can be set at the key stress-bearing parts of the support component, namely point A, point B, point C, and point D, to verify the effect of the body weight of the support component and the thickness of the bracket on the multiple stress points. The influence of stress distribution on stress value.

[0102] Fig.10 The weight of the X-axis support component provided by the present invention and the weight of the force point Schematic diagram of stress value distribution; Fig.11 The weight of the Y-axis support component provided by the present invention and the weight of the force point Schematic diagram of stress value distribution; Fig.12 The weight of the Z-axis support component provided by the present invention and the weight of the force point Schematic diagram of stress value distribution. Fig.10 , Fig.11 and Fig.12 As shown, the 1st force point of the supporting component The stress value increases with the increase of the body weight. Therefore, the body weight of the supporting component has an influence on the stress point. The stress distribution has a great influence on the stress value.

[0103] Fig.13 The thickness of the support component of the X-axis provided by the present invention and the 1st of the force point Schematic diagram of stress value distribution; Fig.14 The thickness of the support component of the Y axis provided by the present invention and the stress point are Schematic diagram of stress value distribution; Fig.15 The thickness of the support component of the Z axis provided by the present invention is 1 Schematic diagram of stress value distribution. Fig.13 , Fig.14 and Fig.15 As shown, the 1 of each force point of the supporting component The stress value decreases with the increase of the support thickness. Therefore, the weight of the support component has an influence on the stress point. The stress distribution has a great influence on the stress value.

[0104] Fig.16 This is the second structural schematic diagram of the support component provided by the present invention. Fig.16 As shown, different drop values ​​(also called heights) can be set for the mounting feet of the support components, such as H = 5mm, 15mm, 25mm, 35mm, and 50mm, to verify the effect of the height of the mounting feet of the support components on the 1 of multiple force points. The influence of stress distribution on stress value. Fig.17 This is the third structural diagram of the support component provided by the present invention. Fig.17 As shown, three stress points can be set at the key stress-bearing parts of the support component, such as the maximum stress distribution point (also called MAX1) determined by the overall simulation of the support component, the maximum stress distribution point (MAX2) of the left mounting foot excluding the screw locking point, and the maximum stress distribution point (MAX3) of the right mounting foot excluding the screw locking point, to verify the effect of the height of the mounting foot of the support component on the multiple stress points. The influence of stress distribution on stress value.

[0105] Fig.18 The height of the mounting foot of the X-axis support component provided by the present invention is 1 Schematic diagram of stress value distribution; Fig.19 The height of the mounting foot of the Y-axis support component provided by the present invention is 1 Schematic diagram of stress value distribution; Fig. 20 The height of the mounting foot of the Z-axis support component provided by the present invention is 1 Schematic diagram of stress value distribution. Fig.18 , Fig.19 and Fig. 20 As shown, the 1 of each force point of the supporting component The stress value varies with the height of the mounting foot. Therefore, the height of the mounting foot has a great influence on the stress point. The stress distribution has a great influence on the stress value.

[0106] In summary, the second parameters to be optimized adopted in this embodiment have a certain influence on the supporting strength of the supporting component. Therefore, by optimizing the configuration of the second parameters to be optimized, the reliability and lightness of the bracket design can be effectively improved.

[0107] In some embodiments, step 120 specifically includes: searching the first configuration information and the second configuration information of the vehicle-mounted device to be optimized in the attribute configuration information; searching the temperature boundary conditions, displacement boundary conditions and load boundary conditions of the vehicle-mounted device to be optimized in the boundary condition configuration information; simulating the finite element model according to the first configuration information and the temperature boundary conditions to obtain the node temperature parameters of each target chip under the first parameter to be optimized; simulating the finite element model according to the second configuration information, the displacement boundary conditions and the load boundary conditions to obtain the stress distribution information of the support component under the second parameter to be optimized; wherein the first configuration information includes material model, thermal conductivity information and thermal performance information, and the second configuration information includes material model and material mechanical property information; the temperature boundary conditions include boundary conditions for constraining the ambient temperature of the vehicle-mounted device to be optimized; the displacement boundary conditions include boundary conditions for constraining the installation position of the vehicle-mounted device to be optimized; and the load boundary conditions include boundary conditions for constraining the power spectral density distribution information of the vehicle-mounted device to be optimized.

[0108] Optionally, during the simulation process, for thermal simulation, the property configuration information may be parsed to obtain first configuration information of the vehicle-mounted equipment to be optimized, where the first configuration information of the vehicle-mounted equipment to be optimized includes but is not limited to material model, thermal conductivity information, and thermal performance information.

[0109] Table 3 Data sheet of material model and thermal conductivity information The data sheet of material model and thermal conductivity information is shown in Table 3. The thermal performance information includes but is not limited to information on related heat sources such as power consumption and thermal resistance, which is shown in Table 4. Rja is the thermal resistance between the chip and the environment; Rjb is the thermal resistance between the chip and the PCB; and Rjc is the thermal resistance from the chip to the package shell.

[0110] In addition, the temperature boundary conditions of the vehicle equipment to be optimized are parsed in the boundary condition configuration information, and the temperature boundary conditions include the ambient temperature of the vehicle equipment to be optimized, that is, the air temperature around the thermal simulation, such as the ambient temperature (the conventional requirement for vehicle equipment is 85 degrees), the thermal radiation temperature (which can be kept consistent with the ambient temperature at 85, and the conventional upper shell has an external radiation emissivity of 0.9 due to surface treatment), and the gravity direction (confirmed according to the actual vehicle layout status of the vehicle equipment, generally in the negative Z direction).

[0111] Next, according to the first configuration information and the temperature boundary condition, a thermal simulation is performed on the finite element model to obtain the node temperature parameters of each target chip under the first parameter to be optimized, thereby realizing the thermal simulation.

[0112] Table 4 Data sheet of thermal performance information For mechanical simulation, the attribute configuration information can be parsed to obtain the second configuration information of the vehicle-mounted equipment to be optimized, where the second configuration information of the vehicle-mounted equipment to be optimized includes but is not limited to the material model and material mechanical property information. The material mechanical property information includes but is not limited to elastic modulus, Poisson's ratio, density, yield strength, tensile strength, fatigue strength and elongation, as shown in Table 5.

[0113] In addition, the displacement boundary conditions and load boundary conditions of the vehicle-mounted equipment to be optimized are analyzed and obtained in the boundary condition configuration information. Among them, since the various components of the vehicle-mounted equipment are fastened together with screws, the various components are connected together at the screw positions through one-dimensional rigid (also called 1D rigid) units in the finite element software; at the same time, the installation position of the vehicle-mounted product in the actual vehicle is simulated, and fixed boundary conditions are set at the mounting holes of the mounting feet. Therefore, the displacement boundary conditions include the actual vehicle installation fixed constraints of the vehicle-mounted equipment to be optimized. The setting of the fixed constraints of the supporting components can be determined according to the installation position of the actual vehicle. The specific distribution is as follows: Fig.21 shown.

[0114] Table 5 Data sheet of material model and material mechanical properties information Table 6 Data table of power spectrum density distribution information The load boundary conditions include the power spectral density (PSD) distribution information used for mechanical strength analysis. The specific distribution data table is shown in Table 6.

[0115] Next, the finite element model is mechanically simulated according to the second configuration information, displacement boundary conditions and load boundary conditions to obtain stress distribution information of the support component under the second parameter to be optimized. For example, the random vibration intensity simulation is performed by superimposing the modal module and the random vibration module of the finite element analysis software, wherein the PSD power spectrum density curve needs to be input as the boundary condition input in the random vibration module to simulate the energy input by the bumps of the road during the driving of the actual vehicle, so as to obtain the stress distribution information of the support component under the second parameter to be optimized.

[0116] The method provided in this embodiment integrates attribute configuration information and boundary condition configuration information to accurately simulate the finite element model, thereby effectively obtaining the node temperature parameters of the target chip and the stress distribution information of the supporting components, providing data support for the performance optimization of the vehicle-mounted equipment, thereby helping to improve the overall performance and reliability of the equipment.

[0117] In summary, based on the above embodiments, it can be seen that compared with the prior art that uses simulation tools to perform a one-time safety assessment, there is no lean design for key structural parts such as the upper cover heat dissipation fins and the bracket mounting feet, resulting in a larger product size and weight, increasing product costs while reducing design reliability. The method provided in this embodiment establishes a finite element analysis model of a vehicle-mounted product and sets material properties of each part; applies temperature boundary conditions, displacement boundary conditions, and load boundary conditions to the surface of the finite element analysis model; solves the finite element analysis model according to the material properties and boundary conditions, obtains the node temperature of each key chip through thermal simulation, and obtains the 1 of the mounting bracket of the key force-bearing device through mechanical random vibration simulation. Stress distribution; and the node temperature of the component and the maximum operating temperature parameters of the component are obtained through thermal simulation for comparison. The first step is to ensure the safety of the design; further, for the main fin heat dissipation fin module of the upper cover, the DOE optimization module of thermal simulation is combined to optimize the design to achieve the most reasonable heat dissipation fin height, thickness, and spacing design, to ensure the lean design of the fins under the premise of ensuring the heat dissipation safety of the components, and to reduce the weight and production cost of the upper cover; in addition, the 1 of the mounting bracket of the key stress-bearing parts is obtained through mechanical simulation Stress distribution, extract maximum 3 The stress and fatigue strength of the bracket material are compared to ensure the reliability of the bracket design. In areas with less stress, local hollowing design can be performed to reduce the weight of the entire product; at the same time, the lightweight design of the upper cover fins can reduce the load-bearing requirements of the mounting bracket, further improving the reliability of the mounting bracket design.

[0118] The vehicle-mounted device optimization configuration system provided by the present invention is described below. The vehicle-mounted device optimization configuration system described below and the vehicle-mounted device optimization configuration method described above can be referenced to each other.

[0119] Fig. 22 Schematic diagram of the structure of the vehicle-mounted equipment optimization configuration system provided by the present invention; Fig. 22As shown, the system includes: an acquisition unit 2210 for acquiring a finite element model, attribute configuration information and boundary condition configuration information of the vehicle-mounted device to be optimized; a simulation unit 2220 for simulating the finite element model according to the attribute configuration information and the boundary condition configuration information, and obtaining the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting components in the vehicle-mounted device to be optimized under the second parameter to be optimized; a first optimization unit 2230 for optimizing the first parameter to be optimized according to the node temperature parameter to obtain the first optimized parameter, and optimizing the second parameter to be optimized according to the stress distribution information to obtain the second optimized parameter; a second optimization unit 2240 for optimizing and generating the structural configuration information of the vehicle-mounted device to be optimized according to the first optimization parameter and the second optimization parameter.

[0120] The system provided in this embodiment obtains the finite element model of the vehicle-mounted equipment to be optimized and its attribute configuration information and boundary condition configuration information; and refines and automatically simulates the finite element model based on these configuration information to obtain the node temperature parameters of the target chip under the structural parameters to be optimized of the heat dissipation component, and the stress distribution information of the supporting component under its structural parameters to be optimized; optimizes the first parameter to be optimized based on the node temperature parameter to obtain the first optimized parameter, and optimizes the second parameter to be optimized based on the stress distribution information to obtain the second optimized parameter; finally, based on these optimized parameters, optimizes and generates the structural configuration information of the vehicle-mounted equipment to be optimized, thereby combining the finite element model, design experience and automated simulation process to intelligently optimize the two key design areas of heat dissipation and strength of the vehicle-mounted equipment, which not only significantly improves the efficiency and accuracy of the optimized configuration of the vehicle-mounted equipment, but also ensures the one-time pass rate of the DV test, thereby reducing the problems that may arise in subsequent verification tests and the required number of design improvements and verification test retests, thereby greatly reducing the time and labor costs for optimizing the configuration of the vehicle-mounted equipment.

[0121] The system provided by the present invention is used to execute the above-mentioned method embodiments. Please refer to the above-mentioned embodiments for the specific processes and detailed contents, which will not be repeated here.

[0122] Fig.23 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.23As shown, the electronic device may include: a processor 2310, a communication interface 2320, a memory 2330 and a communication bus 2340, wherein the processor 2310, the communication interface 2320 and the memory 2330 communicate with each other through the communication bus 2340. The processor 2310 may call the logic instructions in the memory 2330 to execute the vehicle-mounted device optimization configuration method, which includes: obtaining the finite element model, attribute configuration information and boundary condition configuration information of the vehicle-mounted device to be optimized; simulating the finite element model according to the attribute configuration information and the boundary condition configuration information to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized; optimizing the first parameter to be optimized according to the node temperature parameter to obtain the first optimized parameter, and optimizing the second parameter to be optimized according to the stress distribution information to obtain the second optimized parameter; optimizing and generating the structural configuration information of the vehicle-mounted device to be optimized according to the first optimized parameter and the second optimized parameter.

[0123] In addition, the logic instructions in the above-mentioned memory 2330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0124] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the vehicle-mounted equipment optimization configuration method provided by the above methods, which includes: obtaining a finite element model, attribute configuration information and boundary condition configuration information of the vehicle-mounted equipment to be optimized; simulating the finite element model according to the attribute configuration information and the boundary condition configuration information to obtain the node temperature parameters of each target chip in the vehicle-mounted equipment to be optimized under the first parameter to be optimized and the stress distribution information of the supporting components in the vehicle-mounted equipment to be optimized under the second parameter to be optimized; optimizing the first parameter to be optimized according to the node temperature parameter to obtain the first optimized parameter, and optimizing the second parameter to be optimized according to the stress distribution information to obtain the second optimized parameter; optimizing and generating the structural configuration information of the vehicle-mounted equipment to be optimized according to the first optimized parameter and the second optimized parameter.

[0125] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the vehicle-mounted equipment optimization configuration method provided by the above-mentioned methods, the method comprising: obtaining a finite element model, attribute configuration information and boundary condition configuration information of the vehicle-mounted equipment to be optimized; simulating the finite element model according to the attribute configuration information and the boundary condition configuration information to obtain the node temperature parameters of each target chip in the vehicle-mounted equipment to be optimized under the first parameter to be optimized and the stress distribution information of the supporting components in the vehicle-mounted equipment to be optimized under the second parameter to be optimized; optimizing the first parameter to be optimized according to the node temperature parameter to obtain the first optimized parameter, and optimizing the second parameter to be optimized according to the stress distribution information to obtain the second optimized parameter; optimizing and generating the structural configuration information of the vehicle-mounted equipment to be optimized according to the first optimized parameter and the second optimized parameter.

[0126] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0127] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing configuration of vehicle-mounted equipment, characterized in that: include: Obtaining the finite element model, attribute configuration information, and boundary condition configuration information of the vehicle-mounted equipment to be optimized; According to the attribute configuration information and the boundary condition configuration information, the finite element model is simulated to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized; According to the node temperature parameter, the first parameter to be optimized is optimized to obtain a first optimized parameter, and according to the stress distribution information, the second parameter to be optimized is optimized to obtain a second optimized parameter; Optimizing and generating structural configuration information of the vehicle-mounted device to be optimized according to the first optimization parameter and the second optimization parameter; The first parameter to be optimized is a structural parameter to be optimized of a heat dissipation component in the vehicle-mounted device to be optimized, and the second parameter to be optimized is a structural parameter to be optimized of the supporting component.

2. The vehicle-mounted equipment optimization configuration method according to claim 1, characterized in that: The step of optimizing the first parameter to be optimized according to the node temperature parameter to obtain a first optimized parameter includes: In the attribute configuration information, searching for the maximum operating temperature parameter of each of the target chips; Constructing a target cost function according to the node temperature parameter, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized; The first parameter to be optimized is optimized according to the target cost function to obtain the first optimized parameter.

3. The vehicle-mounted equipment optimization configuration method according to claim 2, characterized in that: The constructing a target cost function according to the node temperature parameter, the maximum operating temperature parameter, and the size cost corresponding to the first parameter to be optimized includes: Taking the junction temperature parameter of each target chip as less than or equal to the maximum operating temperature parameter of each target chip as a target, constructing a first cost function; A second cost function is constructed with the goal of minimizing the weighted sum of the node temperature parameters of all the target chips; Constructing a third cost function with the goal of minimizing the size cost corresponding to the first parameter to be optimized; The target cost function is constructed by combining the first cost function, the second cost function and the third cost function.

4. The vehicle-mounted equipment optimization configuration method according to any one of claims 1 to 3, characterized in that: After optimizing the first parameter to be optimized according to the node temperature parameter to obtain the first optimized parameter, the method further includes: updating the finite element model according to the first optimization parameter to obtain an updated finite element model; Performing a temperature rise test on a vehicle-mounted device prototype corresponding to the first optimization parameter to obtain a first node temperature parameter of each target chip under the first optimization parameter; Performing a temperature rise test on the updated finite element model to obtain a second node temperature parameter of each target chip under the first optimization parameter; A regression analysis is performed on the error between the first node temperature parameter and the second node temperature parameter, and the attribute configuration information is updated according to the regression analysis result.

5. The vehicle-mounted equipment optimization configuration method according to any one of claims 1 to 3, characterized in that: The step of optimizing the second parameter to be optimized according to the stress distribution information to obtain a second optimized parameter includes: Obtaining stress parameters of different stress-bearing parts of the support component at different positions from the stress distribution information; Among the multiple stress-bearing parts of the support component, locate a first stress-bearing part having a stress parameter greater than a preset stress parameter; In the second parameter to be optimized, a first sub-parameter corresponding to the first stress-bearing part is obtained, and the first sub-parameter is optimized with the goal of optimizing the stress parameters of the first stress-bearing part in different directions to be less than or equal to the preset stress parameters; Determining the second optimized parameter according to the optimized first sub-parameter; Wherein, the preset stress parameter is determined according to the fatigue strength of the supporting component.

6. The vehicle-mounted equipment optimization configuration method according to claim 5, characterized in that: The step of determining the second optimization parameter according to the optimized first sub-parameter includes: Among the multiple stress-bearing parts of the support component, locate a second stress-bearing part having a stress parameter less than or equal to the preset stress parameter; In the second parameter to be optimized, a second sub-parameter corresponding to the second stress-bearing part is obtained, and the second sub-parameter is optimized with the goal that the stress parameter of the second stress-bearing part in different directions is less than or equal to the preset stress parameter and the mass of the supporting component is minimized; The second optimized parameter is determined according to the optimized second sub-parameter and the optimized first sub-parameter.

7. The vehicle-mounted equipment optimization configuration method according to claim 6, characterized in that: The first sub-parameter includes at least one of a thickness configuration parameter, a mounting foot height configuration parameter, a flange height configuration parameter, a chamfer radius configuration parameter, a crack stop groove configuration parameter, a strength configuration parameter, and a rib position configuration parameter; The second sub-parameters include structural lightweight configuration parameters and / or density configuration parameters.

8. The vehicle-mounted equipment optimization configuration method according to any one of claims 1 to 3, characterized in that: The finite element model is simulated according to the attribute configuration information and the boundary condition configuration information to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized, including: In the attribute configuration information, searching for the first configuration information and the second configuration information of the vehicle-mounted device to be optimized; In the boundary condition configuration information, searching for the temperature boundary condition, displacement boundary condition and load boundary condition of the vehicle-mounted equipment to be optimized; Simulating the finite element model according to the first configuration information and the temperature boundary condition to obtain the node temperature parameters of each of the target chips under the first parameters to be optimized; Simulating the finite element model according to the second configuration information, the displacement boundary condition and the load boundary condition to obtain stress distribution information of the support component under the second parameter to be optimized; Wherein, the first configuration information includes material model, thermal conductivity information and thermal performance information, and the second configuration information includes material model and material mechanical property information; The temperature boundary conditions include boundary conditions for constraining the ambient temperature of the vehicle-mounted equipment to be optimized; the displacement boundary conditions include boundary conditions for constraining the installation position of the vehicle-mounted equipment to be optimized; and the load boundary conditions include boundary conditions for constraining the power spectral density distribution information of the vehicle-mounted equipment to be optimized.

9. A vehicle-mounted equipment optimization configuration system, characterized in that: include: An acquisition unit, used to acquire a finite element model, attribute configuration information, and boundary condition configuration information of the vehicle-mounted equipment to be optimized; A simulation unit, configured to simulate the finite element model according to the attribute configuration information and the boundary condition configuration information, to obtain the node temperature parameters of each target chip in the vehicle-mounted device to be optimized under the first parameter to be optimized and the stress distribution information of the supporting component in the vehicle-mounted device to be optimized under the second parameter to be optimized; A first optimization unit is used to optimize the first parameter to be optimized according to the node temperature parameter to obtain a first optimized parameter, and optimize the second parameter to be optimized according to the stress distribution information to obtain a second optimized parameter; A second optimization unit, configured to optimize and generate the structural configuration information of the vehicle-mounted device to be optimized according to the first optimization parameter and the second optimization parameter; The first parameter to be optimized is a structural parameter to be optimized of a heat dissipation component in the vehicle-mounted device to be optimized, and the second parameter to be optimized is a structural parameter to be optimized of the supporting component.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the vehicle-mounted device optimization configuration method as described in any one of claims 1 to 8 is implemented.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle-mounted device optimization configuration method according to any one of claims 1 to 8 is implemented.

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