Combining Warm And Cold Precision Forming Numerical Simulation And Process Optimization Of Complex Cup-shaft Part

With the rapid development of automobile industry and the increasingly fierce market competition, people pay more attention to the vehicle safety performance and comfortable performance requirements. Automotive steering system’s quality affects the performance of vehicle performance directly, Automotive steering screw as an important component of vehicle steering system, its performance which is good or bad affect steering system reliability directly at the same time, will affect the vehicle performance. Automotive steering screw is an typical complex rod-cup part, which it has complex shape and high precision, using the warm and cold combination extrusion processing can meet the requirements of its shape and precision.In this paper, by using the finite element numerical simulation to analyze the vehicle steering screw under the warm and cold combination forming technology, compares the forming processes of automobile steering screw and determine the forming process plan, analyze the die wear of warm extrusion at the same time.First of all, making two feasible processing plans for the automotive steering screw, which is multi-step composite extrusion forming and two-step composite extrusion forming(cup-rod part composite extrusion forming processing).Making thermo-mechanical coupled numerical simulations for the two kinds of process plans by using bulk forming software-Deform, acquires each forming processing procedure’s forming load curve graph, velocity distribution vector graph, and observe the problem in the forming process, to those as comparison standards, to compare the two kinds of processing plans, choosing the two-step composite extrusion forming as the forming plan finally.Second, the wear is the main factor affects the concave die life at the warm extrusion inner hole. Combined with orthogonal test and finite element numerical simulation that is based Archard wear model to analyze the warm extrusion concave’s wear, Apply the concave die’s entrance radius r, mould initial temperature t, mould initial hardness HRC, friction factor m as the concave wear’s four impact factors, and respectively select the four impact factors’ four levels, determined the L16(45) orthogonal experiment plan, through the range analysis and variance analysis, determined the concave die’s entrance radius is 2mm, initial temperature is 350℃, mold hardness is HRC55, friction factor is 0.2 as the optimal combination,applying the optimal parameters combination to make model and numerical simulation analysis, obtained the die wear, and then can forecast the die’s life.Finally, because of the intelligent algorithm’s application and the localized problems of the orthogonal test analysis. Applying the thirty-two date samples that is by the four parameters combination that is influencing die wear and the die wear under the finite element numerical simulation to train the BP neural network, building the relationship between die entrance radius r, initial hardness HRC, initial temperature t, friction factor m and the wear of the concave die wear. Wear as the objective function, through the genetic algorithm to optimize four factors combination, makes the smallest wear of concave die. The results show that compared with the orthogonal experimental method, the maximum wear which is using this method to optimize parameters’ result was reduced by 12.35%, illustrates the design method is feasible.