Issue |
E3S Web Conf.
Volume 601, 2025
The 3rd International Conference on Energy and Green Computing (ICEGC’2024)
|
|
---|---|---|
Article Number | 00027 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/e3sconf/202560100027 | |
Published online | 16 January 2025 |
Comparative study of conventional sliding mode control and integral sliding mode control for a bidirectional dc-dc converter in an electric vehicle charger
LabSIPE at National School of Applied Sciences, Chouaib Doukkali University, EL Jadida 24002, Morocco
* e-mail: Oualifi.k@ucd.ac.maauthor
Bidirectional dc-dc converters are crucial for integrating electric vehicles (EVs) with the electrical grid, facilitating both grid-to-vehicle (G2V) and vehicle to grid (V2G) energy transfers. Nonetheless, effectively controlling bidirectional energy flow poses significant challenges. This study compares two control methods, the conventional sliding mode controller (CSMC) and the integral sliding mode controller (ISMC), as applied to a bidirectional dc-dc converter. The dc-dc converter functions in two distinct modes: during grid to vehicle (G2V), it operates in buck mode to charge the battery using either constant current or constant voltage based on the battery’s voltage level; and during vehicle-to-grid (V2G), it switches to boost mode to discharge battery power into the grid at a constant current. The proposed controllers were simulated using MATLABK/Simulink and compared with a traditional linear PI controller. The simulation results highlight the efficiency and superiority of ISMC over both CSMC and PI control. In particular, ISMC offers superior performance in terms of response time and accuracy.
© The Authors, published by EDP Sciences, 2025
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.