@inproceedings{a2d015de44f14440bb3d9f9768883a3f,
title = "Model Predictive Control for Dual Active Bridge in fast Charging Application of Electric Vehicles",
abstract = "In this paper, a discrete-time model predictive control (MPC) of dual active bridge-based charging system has been deployed and compared to conventional PI controlled system highlighting strength of MPC over conventional PI control. The predictive control algorithm utilises the discrete nature of the full-bridges and predicts the future state of the system. The objective of the MPC is to reduce the cost function by selecting the switching states from a finite set of switching for the converters in the next sample period. Consequently, the corresponding switching state is used as the firing command to the converter. The MPC is applied to control the power flow between the two bridges with an isolation transformer in the middle. The proposed MPC for bi-directional DC-DC converter is simulated with MATLAB Simulink and shows that the amount of reactive power is reduced by avoiding the phase shift between the primary and secondary sides of the high frequency transformer and allows for power transfer at unity power factor. Finally, a performance comparison between MPC and PI control algorithm is performed.",
keywords = "DC-DC converter, electrical vehicles, predictive control",
author = "Mohamed Elkeiy and Ralph Kennel and Ayman Abdel-Khalik and Mohamed Abdelrahem",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 23rd International Middle East Power Systems Conference, MEPCON 2022 ; Conference date: 13-12-2022 Through 15-12-2022",
year = "2022",
doi = "10.1109/MEPCON55441.2022.10021773",
language = "English",
series = "2022 23rd International Middle East Power Systems Conference, MEPCON 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 23rd International Middle East Power Systems Conference, MEPCON 2022",
}