Lightweight Design and Analysis of Steering Knuckle of Formula Student Car Using Topology Optimization Method

The steering knuckle is a crucial component of student racing vehicles, designed by the Formula Society of Automotive Engineers (FSAE). Developing a lightweight (LW) vehicle that meets the requirements of the student formula car presents a challenge. This study presents a LW design of the steering k...

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Bibliographic Details
Main Authors: Ammarul Hasan, Cunhao Lu, Wei Liu
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:World Electric Vehicle Journal
Subjects:
Online Access:https://www.mdpi.com/2032-6653/14/9/233
Description
Summary:The steering knuckle is a crucial component of student racing vehicles, designed by the Formula Society of Automotive Engineers (FSAE). Developing a lightweight (LW) vehicle that meets the requirements of the student formula car presents a challenge. This study presents a LW design of the steering knuckle using the Topology Optimization (TO) approach for the Formula Society of Automotive Engineers (FSAE) competition considering two different mass constraints (40% and 48%). Moreover, the research includes Stress–Life (SN) curves for three materials, structural steel, 4130 steel, and AISI 1020 steel, providing essential insights into the fatigue characteristics of the model. The results compare the three materials and two mass reduction levels, with steel 4130 achieving a significant mass reduction of 42.70%. Additionally, steel 4130 exhibits superior performance in weight reduction, stress, deformation, and safety aspects. The optimized design meets the criteria for strength, stiffness, and safety under various conditions. The fatigue analysis reveals that AISI 1020 and steel 4130 have superior endurance (1 × 10<sup>5</sup> and 2 × 10<sup>5</sup> cycles, respectively). This research provides significant contributions to the development of a LW, high-performance steering knuckle for student formula racing vehicles, highlighting the significance of TO and material selection in achieving optimal outcomes.
ISSN:2032-6653