Optimization of Stamping Process Parameters for Small Curved Beam Parts of Rail Train Based on GA-PSO-BP Algorithm

6005A aluminum alloy is a medium-strength alloy widely used in the aerospace industry and throughout railway applications. The forming limit curve of 6005A aluminum alloy at 350–450 ℃ is obtained by forming limit test and the microstructure was analyzed. Particle swarm optimization (PSO)-BP neural network combined with genetic algorithm optimization method is used to obtain the best hot stamping process parameters for small curved beam parts of high-speed trains, and used to optimize the hot stamping forming parameters of the 6005A aluminum alloy track train small curved beam parts. The optimization results from PSO-BP neural network and genetic algorithm are verified by finite element simulation analysis and forming limit diagram. The results show that the deformation temperature has a great influence on the forming limit of aluminum alloy. The optimal process parameters for hot stamping of 6005A aluminum alloy small curved beam parts were determined: blank holder force is 4.051KN, stamping speed is 141 mm/s, friction coefficient is 0.05, and maximum thinning rate is 21.2%.