Issue |
MATEC Web Conf.
Volume 393, 2024
2nd International Conference on Sustainable Technologies and Advances in Automation, Aerospace and Robotics (STAAAR-2023)
|
|
---|---|---|
Article Number | 02008 | |
Number of page(s) | 8 | |
Section | Design, Development, and Optimization | |
DOI | https://doi.org/10.1051/matecconf/202439302008 | |
Published online | 13 March 2024 |
Design and Modelling of Self standing Electric Scooter
1 Department of Automobile Engineering New Horizon College of Engineering, India
2,3,4 Department of Automobile Engineering New Horizon College of Engineering, India
* Corresponding author: saaimsabeel@gmail.com
This work focuses on the compact design of a self-standing electric scooter, specifically engineered to require minimal parking space. The paper details the design and modelling of an innovative electric scooter that possesses the unique ability to stand on its own, utilizing a footprint smaller than that of a typical umbrella stand when parked. Employing a minimalist design approach, the scooter achieves an aesthetically appealing, simple, and futuristic appearance. The primary objective of this project is to propose a practical and compact electric scooter design by utilizing CATIA V5 software for modelling and ANSYS for required calculations and SolidWorks for visualization,A design that not only enhances efficiency for short-distance travels but also effectively mitigates issues related to traffic congestion and limited parking space.
Key words: Self-Standing / CATIA V5 / Modelling / Electric scooter
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.