Issue |
E3S Web Conf.
Volume 336, 2022
The International Conference on Energy and Green Computing (ICEGC’2021)
|
|
---|---|---|
Article Number | 00058 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/e3sconf/202233600058 | |
Published online | 17 January 2022 |
Design of a versatile diagnostic test bench of an electric vehicle’s powertrain for educational purpose using a Model-based system engineering
1 Green Tech Institute, Mohammed VI Polytechnic University, Benguerir, Morocco
2 Hassan II University of Casablanca, Morocco
* Corresponding author: hicham.elhadraoui@um6p.ma
With the rapid development of the sustained economy, the sales of electric vehicles are increasingly pressing, and today the maintenance has severely impeded the marketing and usage of electric vehicles. The maintenance procedure for electric vehicles is considered a critical process, tell its affect the security and availability directly with the passengers. Many of research efforts are still devoted to develop and innovate on electric traction systems diagnostic and prognostic. Furthermore, in high-quality education, especially engineering education, topics concerning the vital and actual concerns should comprise more than theoretical knowledge, in purpose to close the relationship between the present technology and the student’s environment and provides hands-on engineering experience and training of general engineering skills, in order to avoid non-standard, unskilled maintenance work. The paper presents a first step towards designing a test bench of a fully electric vehicle’s Powertrain used for research and educational purposes using model-based systems engineering (MBSE) and systems modelling language (SysML) thorough the CESAM architecting and modelling framework. As the first step of the system’s design, an operational perspective layout of the diagnostic and prognostic’s test bench is built and presented using this technique.
© The Authors, published by EDP Sciences, 2022
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.