| Issue |
E3S Web Conf.
Volume 61, 2018
International Conference on Renewable Energy (ICREN 2018)
|
|
|---|---|---|
| Article Number | 00007 | |
| Number of page(s) | 13 | |
| DOI | https://doi.org/10.1051/e3sconf/20186100007 | |
| Published online | 31 October 2018 | |
Electronic Differential and Neuro-Fuzzy Sliding Mode Control with Extended State Observer for an Electric Vehicle System
1 RCAM Laboratory, University of Sidi Bel-Abbes, 22000, Algeria
2 University of Mascara, 29000, Algeria
* Corresponding author: faroukspvusto@yahoo.fr
In this paper a neuro-fuzzy-sliding mode control (NFSMC) with extended state observer (ESO) technique; is designed to guarantee the traction of an electric vehicle with two distinct permanent magnet synchronous motor (PMSM). Each PMSM systems (source-convertermotor) are attached to an electronic differential (ED), in order to adjust the senses of direction of the vehicle, and sustain a stable speed by adapting the difference in velocity of each motor-wheel according to the direction in the case of a turn. Two types of controllers are employed by a hybrid control scheme to assure the control and the performance of the vehicle. This hybrid control scheme guarantees the stability of the vehicle by ED, reduces the chattering phenomena in the PMSM electric motor, and improves the disturbance rejection ability which employs tow types of controllers. The neuro-fuzzy sliding mode control on the direct current loop and ESO controller on the speed loop, and the quadratic current loop; taking into account the dynamic of the vehicle. Simulation runs under Matlab/Simulink to assess the efficiency, and strength of the recommended control method on the closed loop system.
© The Authors, published by EDP Sciences, 2018
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.