Optimization of Loading Path for Hydroforming of Asymmetric Curved Tubes Using AMGA

Area of Science:

• Manufacturing Engineering
• Materials Science
• Computational Mechanics

Background:

• Hydroforming performance is sensitive to feed parameters, pressure, and friction, leading to defects like wrinkling and uneven thickness.
• Optimizing these parameters is crucial for defect prevention and achieving desired component geometry in trailing arm hydroforming.

Purpose of the Study:

• To propose a multi-objective optimization method for hydroforming trailing arms.
• To enhance component quality by minimizing wall thinning and defects.
• To validate the optimization scheme through physical experiments.

Main Methods:

• An integrated numerical simulation framework combining the Archive-based Micro Genetic Algorithm (AMGA) and LS-DYNA was developed.
• Optimization objectives included maximum/minimum wall thickness and die-to-workpiece gap.
• Design variables were internal pressure and axial feed velocity, with adaptive adjustment of loading paths.

Main Results:

• The maximum wall thinning rate decreased from 20.4% to 14.8%.
• Wall thickness uniformity improved, and forming defects were significantly suppressed.
• Experimental validation showed a maximum relative error of 7.46% between simulated and measured values.

Conclusions:

• The proposed AMGA-based optimization method effectively optimizes hydroforming loading paths for trailing arms.
• The validated approach ensures reliable engineering applicability and provides insights for similar structural component forming.
• This method enhances component quality by reducing defects and improving wall thickness uniformity.