Integrated FEA framework for chassis design and failure prediction in SAE supra vehicles

This paper will offer a unified strategy to the optimization of the chassis of a Formula SAE Supra car and predict structural failures using machine learning and Finite Element Analysis (FEA). The work demonstrates that computer aided design and analysis used simultaneously are more effective in comparison with the old-fashioned trial and error approach, and they do not affect the high safety standards. The proposed framework evaluates the chassis under the frontal, side, and rear impact conditions under systematic FEA when 2000 N (2 kN) loads are applied to it and then the results of this assessment are used to evaluate the variability of various design variants. The three candidate steels considered in the analysis include AISI 1018, AISI 4130, and AISI 4140 so that the most appropriate material to use in the structure can be identified. The choice of AISI 4130 chromoly steel can be explained by the opportunity to provide maximum Von Mises stress of 367.81 MPa, peak equivalent strain of mm/mm and maximum deformation of 1.2004 mm during the specified load cases, which met the requirements of the strengths and deformations.