| Abstract: |
The leaf spring suspension system in heavy-duty commercial vehicles is subjected to severe static and dynamic loads that demand simultaneous optimization of stress distribution, deflection control, and structural mass. This study presents a fully integrated finite element based design optimization framework that combines high-fidelity nonlinear three-dimensional simulation in ANSYS Workbench R24 with a Taguchi L27 orthogonal array and analysis of variance for a parabolically tapered leaf spring designed for a 25-ton-class tractor-trailer rear suspension. The candidate material is SUP-9 silico-manganese spring steel, selected for its superior fatigue strength relative to conventional EN-45 grade. Five control factors taper ratio, root thickness, leaf width, span length, and material grade are systematically varied across three levels each, yielding 27 finite element simulations supported by a rigorous mesh convergence study and contact validation. Results indicate that root thickness contributes 48.6 percent to the variance in maximum von Mises stress, followed by taper ratio at 22.1 percent and leaf width at 11.4 percent. The Pareto chart of ANOVA contributions confirms that the three dominant factors account for 82.1 percent of the variance crossing the 80 percent threshold for vital-few classification. The optimum factor combination A2 B3 C3 D1 E3 reduces maximum stress to 487 MPa (against a yield-derived allowable of 612 MPa for SUP-9) and reduces structural mass by 31.7 percent compared with the conventional ten-leaf assembly. A confirmation simulation demonstrates an S/N improvement of 3.18 dB, within 1.9 percent of the additive prediction. |
