Optimizing Front Axle Design for Heavy Commercial Vehicles: A Comprehensive Analysis of Structural and Mechanical Properties

2023-01-5076

10/31/2023

Features
Event
Automotive Technical Papers
Authors Abstract
Content
This study intends to improve the design of front axles for heavy commercial vehicles, with a major goal of reducing weight while maintaining mechanical strength. The front axle is critical in supporting the weight of the vehicle and facilitating steering while effectively absorbing shocks generated by differences in road surfaces. To achieve these requirements, a front axle beam that minimizes weight, fuel consumption, and stress on the load-carrying member must be designed. In this work, finite element analysis (FEA) techniques are used using CATIA software to assess the structural and mechanical attributes of several front axle designs. The purpose is to pick the best front axle shape depending on specific load situations and driving torque needs. The influence of alternative component shapes on stress and strain distribution is evaluated using surface changes and ANSYS Workbench numerical simulation software. Furthermore, the impact of these structural changes on the mechanical characteristics of the front axle is carefully investigated. The findings of this study will help to shape front axle designs that strike a compromise between weight reduction and mechanical strength, therefore improving the performance and efficiency of big commercial vehicles. This study gives useful insights into optimizing front axle designs by employing modern engineering analytical techniques, which may lead to increased fuel efficiency and lower vehicle maintenance costs.
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DOI
https://doi.org/10.4271/2023-01-5076
Pages
7
Citation
Sivaraman, P., Ilakiya, P., Prabhu, M., Ajayan, A. et al., "Optimizing Front Axle Design for Heavy Commercial Vehicles: A Comprehensive Analysis of Structural and Mechanical Properties," SAE Technical Paper 2023-01-5076, 2023, https://doi.org/10.4271/2023-01-5076.
Additional Details
Publisher
Published
Oct 31, 2023
Product Code
2023-01-5076
Content Type
Technical Paper
Language
English