The clutch adaptive model uses a layered parallel mode in which the product is organically assembled from parts and components, and the components are assembled from a set of parts in a specific assembly relationship. Therefore, the product structure tree model can be used to represent the product. The root node in the tree represents the product (component), the branch node and the leaf node represent the component (sub-component) and the part. The clutch adaptive product model framework constructed in this paper is shown. The three-layer structure is: product adaptive model layer, component adaptive model layer, and part adaptive model layer <2>.
In the product adaptive model layer, the class library, functions and methods provided by the AML language are used to establish a cost model in a "plug and play" manner, and a manufacturing model, a sales model, and an assembly model are produced. The cost model uses the capture function to correlate with each design action and reacts to the product cost budget through the correlation of cost calculations. The assembly model includes the configuration relationship of the cover assembly, the driven disk assembly, and the operating mechanism, and the relationship between the components is defined by the internal constraint mechanism of the AML. Based on the cost model, the sales model and the manufacturing model seamlessly integrate the external sales model and manufacturing method application into the product adaptive model layer through the AML virtual layer architecture.
The component adaptive model layer includes an analysis model, a manufacturing model, a detection model, and an assembly model. The manufacturing model and the assembly model are modeled according to the implementation of the product adaptive model layer. The detection model of the component adaptive model layer is established by calling the PowerINSPECT software through the AML virtual layer. The analysis model uses the AML language to build an AML analysis framework, and defines the mesh type, size, structural analysis load, boundary conditions, material properties, etc. in the AML analysis framework. The external mesher is called by the virtual layer to automatically divide the mesh, and the external solver is automatically called through the virtual layer, and the analysis model is not required to be built into the external analysis tool. In this system, PATRAN is used as the mesh divider and NAS2TRAN is used as the external solver.
The part adaptive model layer includes an analysis model, a manufacturing model, a detection model, and a geometric model. The geometric model is the core of the clutch adaptive model. The AML advanced geometry module has been seamlessly integrated with the geometric kernel of Shapes, Parasolid and ACIS (3D geometric modeling search engine based on object-oriented software technology) to establish a feature-based parametric geometric model. The geometric kernel of AML integration supports complex Boolean operations to create complex geometric models such as clutch covers, diaphragm springs, friction plates and other geometric models. The other models of this layer are built in the same way as the upper two layers. The swarm intelligence optimization algorithm for the optimization design of the part structure parameters is encapsulated in each part geometric model.
According to the characteristics of the clutch design and the actual application, the design flow of the system adopts the serial mode. The clutch design flow is as shown in the figure. It mainly includes three stages: clutch cover assembly design, clutch driven disc assembly design and operation. Institutional design.
The designer inputs vehicle (design) parameters, including vehicle selection, vehicle parameters, engine parameters, transmission parameters, spline parameters, and separation bearing parameters. According to the input design parameters, the initial calculation of the torque capacity and the life of the friction lining, according to the initial calculation results, the system retrieves the existing cover assembly instance library. If there is a cover assembly that meets the design requirements, the cover is obtained from the cover assembly instance library. The selection and configuration of the cover, instantiate the cover assembly adaptive model. Then according to the selection and configuration, the corresponding part adaptive model is extracted from the parts database, the part selection and configuration is generated, and the 3D parametric model of the part is submitted to the AML advanced geometry module. The part adaptive model utilizes the AML virtual layer seamlessly. The integrated external application tools and modules are used to obtain the analysis model, manufacturing model, and inspection model of the cover assembly part adaptive model. If there is no cover assembly that meets the design requirements, the system needs to redesign the cover assembly. The original design parameters of the input are used to initially determine the basic structure of the clutch, including the type of clutch (push, pull) and form (single Selection of disc, double disc), selection of force transmission mode of pressure plate, selection of driven disc type, selection of follower type, selection of friction disc material, fastening method of driven piece and friction plate, and selection of separation bearing type . Then determine the basic parameters of the clutch, including the outer diameter D of the friction plate, the unit pressure, and the backup coefficient. Then the structural design of the cover assembly is carried out. The structural parameters of the key parts are optimized and calculated by the intelligent optimization algorithm. The calculated part structure size is submitted to the AML advanced geometry module to create a 3D parametric model of the part. The part adaptive model uses the AML virtual layer seamlessly integrated external application tool and module to obtain the analysis model of the cover assembly part adaptive model. , manufacturing model, test model part.
Structural parameter intelligent optimization design In the part adaptive model layer, the structural parameter design of the part is solved by intelligent optimization method. Researchers have used different optimization methods to solve <3~5>. In this paper, the particle swarm optimization algorithm in the swarm intelligence optimization algorithm is used to optimize the multi-objective design of key part structure parameters.
The application example applies the above clutch adaptive model and design flow to retrofit the DS350 product for automotive diaphragm spring clutch. After the design requirements are input, the modified design results are obtained according to the serial design flow using the clutch adaptive product model framework. The adaptive geometry model of the designed clutch cover assembly and driven disc assembly is shown.
Conclusion The design example verification shows that based on the product adaptive model modeling method proposed in this paper, the clutch adaptive model established by AML tool software can meet the needs of different stages in clutch design. The knowledge-based model provides the possibility of intelligent design of clutch. . The successful application of the particle swarm optimization algorithm in the design of the clutch part structure ensures the optimal design of the part structure.
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