Design and Optimization of an Electric Car Chassis and Body Using Structural Analysis and Computational Fluid Dynamics

2022-01-5015

03/16/2022

Features
Event
Automotive Technical Papers
Authors Abstract
Content
The transition from traditional gasoline-powered automobiles to electric vehicles has taken time. Two significant challenges of engine-powered vehicles are greenhouse gas emissions and fuel economy. Working with lightweight materials has emerged as a critical area for improvement in the automotive industry in today’s world. The most efficient method for increasing power output is to reduce the weight of vehicle components. Composite materials have significantly benefited from research and development because they are stronger, more recyclable, and easier to integrate into vehicles. The primary goal of this research is to design the body and chassis frame of a two-seater electric car. A computational fluid dynamics (CFD) analysis was performed to determine the body’s drag coefficient and structural analysis to obtain the frontal impact and torsional rigidity of the chassis to develop a practical electric car design. The design was carried out with the help of CATIA V5 software, while the analysis was performed using ANSYS 19.2. A comparative analysis of the chassis was undertaken by incorporating three different materials: traditional steel, i.e., Stainless Steel 304L, Aluminum Alloy (AA) 7075-T6, T300 Carbon Fiber Composite. The energy efficiency of the car for the three materials is also computed. The chassis made from AA 7075-T6 shows a net weight reduction of 23.1%, along with T300 Composite showing a weight reduction of 65.1% compared to the traditional Steel 304L, which are within the optimum weight range to be used as a chassis.
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DOI
https://doi.org/10.4271/2022-01-5015
Pages
9
Citation
Aiyan, M., Sagar, S., and Raghav S., S., "Design and Optimization of an Electric Car Chassis and Body Using Structural Analysis and Computational Fluid Dynamics," SAE Technical Paper 2022-01-5015, 2022, https://doi.org/10.4271/2022-01-5015.
Additional Details
Publisher
Published
Mar 16, 2022
Product Code
2022-01-5015
Content Type
Technical Paper
Language
English