Local parametric modeling and optimizing method, device and equipment for automobile air conditioner pipeline

Abstract

The invention discloses a local parametric modeling and optimizing method, device and equipment for an automobile air conditioner pipeline, and relates to the technical field of automobile air conditioner system optimizing.The method comprises the steps that a pipeline model of an air conditioner system is obtained, a to-be-optimized area is deleted, and the pipeline model with the to-be-optimized area deleted is imported into simulation software; re-modeling the to-be-optimized area to obtain a pipeline local model, and fusing the pipeline local model with the pipeline model imported into the simulation software to obtain a fused model; selecting model parameters for optimizing the local model of the pipeline, and setting the model parameters to obtain a plurality of pipeline performance optimization schemes; and performing performance simulation calculation on the fused model based on a pipeline performance optimization scheme, and determining an optimal pipeline performance optimization scheme according to a simulation result. The optimization time of the automobile air conditioner pipeline can be shortened, and the optimal design scheme of the pipeline can be quickly obtained.

Description

Technical Field

[0001] The present application relates to the technical field of automobile air-conditioning system optimization, and in particular to a method, device and equipment for local parametric modeling and optimization of automobile air-conditioning ducts. Background Art

[0002] Car air conditioners are used to control the temperature, humidity, air cleanliness and air flow in the car compartment to the optimal state, provide passengers with a comfortable riding environment, reduce travel fatigue, and create good driving conditions for the driver. They play an important role in safe driving. They generally include refrigeration devices, heating devices and ventilation devices.

[0003] The defrosting, blowing surface and blowing foot performance of automobile air conditioners are important performances in automobile CFD (Computational Fluid Dynamics) analysis, and are indicators directly facing customer perception, and have very high requirements for performance in this aspect. However, the current simulation analysis of automobile air conditioner performance has problems such as too long optimization iteration time and failure to optimize in time to meet performance goals. Summary of the invention

[0004] The present application provides a method, device and equipment for local parametric modeling and optimization of automobile air-conditioning ducts, which can reduce the optimization time of automobile air-conditioning ducts and quickly obtain the optimal design solution for the ducts.

[0005] In a first aspect, an embodiment of the present application provides a method for local parametric modeling and optimization of an automobile air-conditioning duct, the method comprising:

[0006] Obtain the pipeline model of the air conditioning system and delete the area to be optimized, and import the pipeline model with the area to be optimized deleted into the simulation software;

[0007] Remodeling the area to be optimized to obtain a local pipeline model, and fusing the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model;

[0008] Selecting model parameters for optimizing the local model of the pipeline, setting the model parameters to obtain multiple pipeline performance optimization solutions;

[0009] Based on the pipeline performance optimization plan, the performance simulation calculation of the fused model is carried out, and the optimal pipeline performance optimization plan is determined according to the simulation results.

[0010] In combination with the first aspect, in one implementation, obtaining a pipeline model of the air conditioning system and deleting the area to be optimized, and importing the pipeline model after deleting the area to be optimized into the simulation software specifically includes:

[0011] Obtaining a pipeline model of the air conditioning system to be optimized and analyzed, and determining and deleting a region to be optimized in the pipeline model based on performance influencing factors;

[0012] Import the pipeline model after deleting the area to be optimized into star-ccm+.

[0013] In combination with the first aspect, in one implementation, remodeling the area to be optimized to obtain a local pipeline model, and fusing the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model, specifically includes:

[0014] In star-ccm+, the boundary of the pipeline model cross section is set as the application fixed constraint, and the area to be optimized is remodeled based on the original design parameters of the area to be optimized to obtain the local model of the pipeline;

[0015] The local pipeline model is fused with the cross-section boundary of the pipeline model imported into star-ccm+ to obtain a fused model.

[0016] In combination with the first aspect, in one implementation, after obtaining the fused model, the method further includes:

[0017] Import the fused model into the design manager of star-ccm+;

[0018] Set up performance indicator data result reports and performance indicator scenario cloud charts in the Design Manager.

[0019] In combination with the first aspect, in one implementation, the selecting of model parameters for optimizing the local pipeline model and setting of the model parameters to obtain multiple pipeline performance optimization solutions specifically includes:

[0020] Select model parameters for optimizing the local pipeline model based on performance influencing factors, and set the values ​​of the model parameters;

[0021] Different values ​​of the selected model parameters are arranged and combined to obtain multiple pipeline performance optimization solutions.

[0022] In combination with the first aspect, in one embodiment, the setting of the value of the model parameters is specifically: setting the value range and the number of values ​​of each selected model parameter, so as to select a specific number of parameter values ​​within the value range based on the number of values.

[0023] In combination with the first aspect, in one implementation, the pipeline performance optimization scheme is used to perform performance simulation calculation on the fused model, and the optimal pipeline performance optimization scheme is determined according to the simulation results, specifically including:

[0024] Based on star-ccm+, combined with the pipeline performance optimization scheme, the performance simulation calculation of the fused model is carried out to obtain the simulation results corresponding to each pipeline performance optimization scheme;

[0025] Based on the simulation results, the optimal pipeline performance optimization plan is determined.

[0026] In combination with the first aspect, in one implementation, after determining the optimal pipeline performance optimization solution, the method further includes:

[0027] According to the determined optimal pipeline performance optimization scheme, the values ​​of the model parameters corresponding to the optimal pipeline performance optimization scheme are obtained to achieve the optimization of the air conditioning pipeline.

[0028] In a second aspect, an embodiment of the present application provides a local parametric modeling and optimization device for an automobile air-conditioning duct, the local parametric modeling and optimization device for an automobile air-conditioning duct comprising:

[0029] A processing module, which is used to obtain a pipeline model of the air conditioning system and delete the area to be optimized, and import the pipeline model with the area to be optimized deleted into the simulation software;

[0030] A modeling module, which is used to remodel the area to be optimized to obtain a local pipeline model, and fuse the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model;

[0031] A selection module is used to select model parameters for optimizing the local model of the pipeline, and to set the model parameters to obtain multiple pipeline performance optimization solutions;

[0032] The execution module is used to perform performance simulation calculations on the fused model based on the pipeline performance optimization solution, and determine the optimal pipeline performance optimization solution based on the simulation results.

[0033] In a third aspect, an embodiment of the present application provides a local parametric modeling and optimization device for automobile air-conditioning ducts, wherein the local parametric modeling and optimization device for automobile air-conditioning ducts comprises a processor, a memory, and a local parametric modeling and optimization program for automobile air-conditioning ducts stored in the memory and executable by the processor, wherein when the local parametric modeling and optimization program for automobile air-conditioning ducts is executed by the processor, the steps of the above-mentioned local parametric modeling and optimization method for automobile air-conditioning ducts are implemented.

[0034] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0035] (1) Through the calculation and operation of computer software, all optimization schemes can be automatically generated and the results of all optimization schemes can be calculated and output at the same time. This can not only quickly produce optimization schemes, but also save a lot of optimization time, driving design engineers to more quickly clarify the performance of each optimization scheme during the design and development stage;

[0036] (2) Local parametric modeling is performed in star-ccm+ for the local areas that have a greater impact on the performance indicators. The optimization scheme composed of different combinations of optimization design parameters is automatically generated. The results of all optimization schemes are calculated simultaneously and the optimal performance scheme is selected. This can greatly reduce the optimization time of the automobile air-conditioning ducts and obtain the optimal design scheme of the ducts in a very short time. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of the process of local parametric modeling and optimization method of automobile air conditioning ducts in this application;

[0038] Figure 2 This is a schematic diagram of the functional modules of the device for local parametric modeling and optimization of automobile air-conditioning ducts in this application;

[0039] Figure 3 This is a schematic diagram of the hardware structure of the local parametric modeling and optimization equipment for automobile air-conditioning ducts in this application. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0041] On the first aspect, the embodiment of the present application provides a local parametric modeling and optimization method for automobile air-conditioning ducts. In view of the problems existing in the current simulation analysis of the performance of the air ducts of automobile air-conditioning systems, such as the single optimization and analysis means, basically the modification of the entire duct, the need for re-modeling, replacement and re-analysis, etc., according to the structural design principles of automobile air-conditioning ducts, based on the star-ccm+ fluid analysis software, an overall flow field CFD analysis model is established and the local duct model therein is parametrically modeled using star-3D, so that schemes with different parameters for the local ducts can be automatically generated, and all schemes can be calculated at the same time to select the optimal performance, so as to obtain the optimal local duct design, thereby greatly reducing the optimization time.

[0042] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the method for local parametric modeling and optimization of automobile air conditioning ducts in this application. Figure 1 As shown in the figure, the local parametric modeling and optimization method of automobile air conditioning duct includes:

[0043] S1: Obtain a pipe model of the air-conditioning system and delete the area to be optimized, and import the pipe model with the area to be optimized deleted into the simulation software; that is, for the pipe model of the air-conditioning system in the passenger compartment and other locations created by other model design software, delete the area to be optimized in the pipe model, and then import the pipe model with the area to be optimized deleted into the simulation software.

[0044] Further, in one embodiment, the pipeline model of the air conditioning system is obtained and the area to be optimized is deleted, and the pipeline model with the area to be optimized deleted is imported into the simulation software, specifically including:

[0045] S101: Obtain a pipeline model of the air conditioning system to be optimized and analyzed, determine and delete the area to be optimized in the pipeline model based on performance influencing factors;

[0046] The area to be optimized may be determined based on historical experience data, and based on the relevant performance influencing factors of the air-conditioning system pipes, the area that has a greater impact on the air-conditioning performance may be selected as the area to be optimized.

[0047] S102: Import the pipeline model after deleting the area to be optimized into STAR-CCM+. STAR-CCM+ is a new generation CFD solver developed based on the numerical technology of continuum mechanics.

[0048] Specifically, the local area in the air-conditioning system pipeline that has the greatest impact on air-conditioning performance is evaluated as the area to be optimized, and then the local area that needs to be optimized is deleted in the pipeline model. By identifying the area that is most sensitive to performance, there is no need to remodel the entire model later, and only the area to be optimized needs to be remodeled, thereby saving modeling time.

[0049] S2: remodeling the area to be optimized to obtain a local pipeline model, and fusing the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model;

[0050] Furthermore, in one embodiment, the area to be optimized is remodeled to obtain a local pipeline model, and the local pipeline model is fused with the pipeline model imported into the simulation software to obtain a fused model, which specifically includes:

[0051] S201: In star-ccm+, the boundary of the truncation surface of the pipeline model is set as an application fixed constraint, and the area to be optimized is remodeled based on the original design parameters of the area to be optimized to obtain a local model of the pipeline;

[0052] S202: Fusing the local pipeline model with the cross-section boundary of the pipeline model imported into star-ccm+ to obtain a fused model.

[0053] Since star-ccm+ cannot read the design parameters set by other modeling software during modeling, it is necessary to rebuild the model of the area to be optimized in star-ccm+, import the pipeline model after deleting the area to be optimized into star-ccm+, set the boundary of the deleted area in star-3D as the application fixed constraint, re-model the area to be optimized and apply the model parameters. For the model parameters of the area to be optimized, the design parameter values ​​used during modeling can be changed to automatically reproduce the changed model. This step saves the process of re-optimizing the overall model and can automatically generate a local model that has the greatest impact on performance.

[0054] The local model of the pipeline is merged with the boundary of the pipeline model with the area to be optimized deleted to ensure the integrity of the pipeline, establish the overall mesh and import it into the design manager of star-ccm+.

[0055] Furthermore, after obtaining the fused model, the process also includes: importing the fused model into the design manager of star-ccm+; and setting the performance indicator data result report and the performance indicator scenario cloud map in the design manager. That is, the desired performance indicator data result report and the performance indicator scenario cloud map are preset in the design manager.

[0056] S3: selecting model parameters for optimizing the local model of the pipeline, setting the model parameters and obtaining multiple pipeline performance optimization solutions;

[0057] Furthermore, in one embodiment, model parameters for optimizing the local model of the pipeline are selected, and the model parameters are set to obtain multiple pipeline performance optimization solutions, specifically including:

[0058] S301: selecting model parameters for optimizing the local pipeline model based on performance influencing factors, and setting values ​​of the model parameters;

[0059] The setting of the values ​​of the model parameters is specifically: setting the value range and the number of values ​​of each selected model parameter, so as to select a specific number of parameter values ​​within the value range based on the number of values;

[0060] S302: Arrange different values ​​of the selected model parameters and combine them to obtain multiple pipeline performance optimization solutions.

[0061] Specifically, according to the factors that affect the performance of the air conditioning system pipeline, the corresponding parameters of the local pipeline model are selected, that is, in the design research function of the design manager, the model parameters used to optimize the local pipeline model are selected, and then the value range and number of the model parameters are set. The design manager will automatically arrange the different values ​​of each model parameter and combine them to obtain multiple pipeline performance optimization solutions. By combining all pipeline performance optimization solutions, a large amount of accumulated optimization time for single iterative optimization can be saved, and all optimization solutions can be output at one time.

[0062] S4: Perform performance simulation calculation on the fused model based on the pipeline performance optimization plan, and determine the optimal pipeline performance optimization plan based on the simulation results.

[0063] Furthermore, in one embodiment, a performance simulation calculation is performed on the fused model based on the pipeline performance optimization solution, and an optimal pipeline performance optimization solution is determined according to the simulation results, specifically including:

[0064] S401: Based on star-ccm+, combined with the pipeline performance optimization solution, the performance simulation calculation of the fused model is performed to obtain the simulation results corresponding to each pipeline performance optimization solution;

[0065] S402: Determine the best pipeline performance optimization solution based on the simulation results.

[0066] Specifically, by combining all pipeline performance optimization solutions obtained through star-ccm+ and performing performance simulation calculations on the fused model, we can obtain the simulation results corresponding to each pipeline performance optimization solution, that is, the air conditioning performance results corresponding to each pipeline performance optimization solution, and then select the optimal result as the final pipeline performance optimization solution.

[0067] Furthermore, after determining the optimal pipeline performance optimization scheme, the method further includes: obtaining the values ​​of the model parameters corresponding to the optimal pipeline performance optimization scheme according to the determined optimal pipeline performance optimization scheme, so as to optimize the air conditioning pipeline. Specifically, the values ​​of the model parameters corresponding to the selected optimal pipeline performance optimization scheme are used to optimize the air conditioning pipeline of the actual vehicle.

[0068] According to the structural design principles of automobile air-conditioning ducts, this application establishes an overall flow field CFD analysis model based on star-ccm+ fluid analysis software and uses star-3D to perform parametric modeling on the local duct model, so as to automatically generate schemes with different parameters for the local ducts, and simultaneously calculate all schemes to select the optimal performance, thereby obtaining the optimal local duct design, thereby greatly reducing the optimization time.

[0069] The local parametric modeling and optimization method of the automobile air-conditioning duct in the embodiment of the present application can automatically generate all optimization schemes and simultaneously calculate and output the results of all optimization schemes through the calculation and operation of computer software, which can not only quickly produce optimization schemes, but also save a lot of optimization time, and drive design engineers to more quickly clarify the performance of each optimization scheme in the design and development stage; local parametric modeling is performed in star-ccm+ for the identified local areas that have a greater impact on the performance indicators, and optimization schemes composed of different combinations of optimization design parameters are automatically generated. The results of all optimization schemes are calculated simultaneously and the optimal performance scheme is selected, which can greatly reduce the optimization time of the automobile air-conditioning duct, and the optimal design scheme of the duct can be obtained in a very short time; the optimization method described in the present application can be applied to any local area of ​​the automobile air-conditioning duct, suitable for achieving any automobile air-conditioning performance and obtaining all duct design schemes that meet the performance, and can better guide design engineers to perform product optimization design of automobile air-conditioning ducts.

[0070] In a second aspect, an embodiment of the present application also provides a local parametric modeling and optimization device for automobile air-conditioning ducts.

[0071] In one embodiment, referring to Figure 2 , Figure 2 This is a functional module diagram of the device for local parametric modeling and optimization of automobile air conditioning ducts in this application. Figure 2 As shown, the local parametric modeling and optimization device for automobile air-conditioning ducts includes: a processing module, a modeling module, a selection module, and an execution module.

[0072] The processing module is used to obtain the pipeline model of the air-conditioning system and delete the area to be optimized, and import the pipeline model with the deleted area to be optimized into the simulation software; the modeling module is used to re-model the area to be optimized to obtain a local pipeline model, and fuse the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model; the selection module is used to select model parameters for optimizing the local pipeline model, and set the model parameters to obtain multiple pipeline performance optimization schemes; the execution module is used to perform performance simulation calculations on the fused model based on the pipeline performance optimization scheme, and determine the optimal pipeline performance optimization scheme according to the simulation results.

[0073] Among them, the functional implementation of each module in the above-mentioned automobile air-conditioning duct local parametric modeling and optimization device corresponds to the various steps in the above-mentioned automobile air-conditioning duct local parametric modeling and optimization method embodiment, and its functions and implementation processes will not be repeated here one by one.

[0074] In a third aspect, an embodiment of the present application provides a local parametric modeling and optimization device for automobile air-conditioning ducts. The local parametric modeling and optimization device for automobile air-conditioning ducts can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0075] Reference Figure 3 , Figure 3 The hardware structure diagram of the vehicle air conditioning duct local parametric modeling and optimization device involved in the embodiment of the present application is shown in FIG. In the embodiment of the present application, the vehicle air conditioning duct local parametric modeling and optimization device may include a processor, a memory, a communication interface, and a communication bus.

[0076] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0077] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the automobile air conditioning duct local parametric modeling and optimization device, and the interface used to realize the interconnection of the automobile air conditioning duct local parametric modeling and optimization device with other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, an optical fiber interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0078] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0079] The processor may be a general-purpose processor, which may call the local parametric modeling and optimization program of the automobile air-conditioning duct stored in the memory, and execute the local parametric modeling and optimization method of the automobile air-conditioning duct provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the local parametric modeling and optimization program of the automobile air-conditioning duct is called may refer to the various embodiments of the local parametric modeling and optimization method of the automobile air-conditioning duct of the present application, which will not be repeated here.

[0080] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0081] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0082] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0083] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0084] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0085] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0086] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A local parametric modeling and optimization method for automobile air conditioning ducts, characterized in that: The local parametric modeling and optimization method of automobile air conditioning pipeline includes: Obtain the pipeline model of the air conditioning system and delete the area to be optimized, and import the pipeline model with the area to be optimized deleted into the simulation software; Remodeling the area to be optimized to obtain a local pipeline model, and fusing the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model; Selecting model parameters for optimizing the local model of the pipeline, setting the model parameters to obtain multiple pipeline performance optimization solutions; Based on the pipeline performance optimization plan, the performance simulation calculation of the fused model is carried out, and the optimal pipeline performance optimization plan is determined according to the simulation results.

2. A method for local parametric modeling and optimization of automobile air conditioning ducts according to claim 1, characterized in that: The step of obtaining the pipeline model of the air conditioning system and deleting the area to be optimized, and importing the pipeline model after deleting the area to be optimized into the simulation software specifically includes: Obtaining a pipeline model of the air conditioning system to be optimized and analyzed, and determining and deleting a region to be optimized in the pipeline model based on performance influencing factors; Import the pipeline model after deleting the area to be optimized into star-ccm+.

3. A method for local parametric modeling and optimization of automobile air conditioning ducts as claimed in claim 2, characterized in that: The remodeling of the area to be optimized to obtain a local pipeline model, and fusing the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model, specifically includes: In star-ccm+, the boundary of the pipeline model cross section is set as the application fixed constraint, and the area to be optimized is remodeled based on the original design parameters of the area to be optimized to obtain the local model of the pipeline; The local pipeline model is fused with the cross-section boundary of the pipeline model imported into star-ccm+ to obtain a fused model.

4. A method for local parametric modeling and optimization of automobile air conditioning ducts as claimed in claim 3, characterized in that: After obtaining the fused model, it also includes: Import the fused model into the design manager of star-ccm+; Set up performance indicator data result reports and performance indicator scenario cloud charts in the Design Manager.

5. The method for local parametric modeling and optimization of automobile air conditioning ducts according to claim 1, characterized in that: The selecting of model parameters for optimizing the local pipeline model and setting of the model parameters to obtain multiple pipeline performance optimization solutions specifically includes: Select model parameters for optimizing the local pipeline model based on performance influencing factors, and set the values ​​of the model parameters; Different values ​​of the selected model parameters are arranged and combined to obtain multiple pipeline performance optimization solutions.

6. A method for local parametric modeling and optimization of automobile air conditioning ducts as claimed in claim 5, characterized in that: The setting of the values ​​of the model parameters is specifically: setting the value range and the number of values ​​of each selected model parameter, so as to select a specific number of parameter values ​​within the value range based on the number of values.

7. A method for local parametric modeling and optimization of automobile air conditioning ducts as claimed in claim 5, characterized in that: The pipeline performance optimization scheme is based on which the fused model is simulated and calculated, and the optimal pipeline performance optimization scheme is determined according to the simulation results, specifically including: Based on star-ccm+, combined with the pipeline performance optimization scheme, the performance simulation calculation of the fused model is carried out to obtain the simulation results corresponding to each pipeline performance optimization scheme; Based on the simulation results, the optimal pipeline performance optimization plan is determined.

8. A method for local parametric modeling and optimization of automobile air conditioning ducts as claimed in claim 7, characterized in that: After determining the best pipeline performance optimization plan, it also includes: According to the determined optimal pipeline performance optimization scheme, the values ​​of the model parameters corresponding to the optimal pipeline performance optimization scheme are obtained to achieve the optimization of the air conditioning pipeline.

9. A local parametric modeling and optimization device for automobile air conditioning ducts, characterized in that: The automobile air conditioning pipeline local parameterized modeling and optimization device comprises: A processing module, which is used to obtain a pipeline model of the air conditioning system and delete the area to be optimized, and import the pipeline model with the area to be optimized deleted into the simulation software; A modeling module, which is used to remodel the area to be optimized to obtain a local pipeline model, and fuse the local pipeline model with the pipeline model imported into the simulation software to obtain a fused model; A selection module is used to select model parameters for optimizing the local model of the pipeline, and to set the model parameters to obtain multiple pipeline performance optimization solutions; The execution module is used to perform performance simulation calculations on the fused model based on the pipeline performance optimization solution, and determine the optimal pipeline performance optimization solution based on the simulation results.

10. A local parametric modeling and optimization device for automobile air conditioning ducts, characterized in that: The local parametric modeling and optimization device for automobile air-conditioning ducts comprises a processor, a memory, and a local parametric modeling and optimization program for automobile air-conditioning ducts stored in the memory and executable by the processor, wherein when the local parametric modeling and optimization program for automobile air-conditioning ducts is executed by the processor, the steps of the local parametric modeling and optimization method for automobile air-conditioning ducts as described in any one of claims 1 to 8 are implemented.

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