@inproceedings{f846031eb6ce44269deac71322e82f90,
title = "Time-delayed model predictive direct power control for vehicle to grid and grid to vehicle applications",
abstract = "This paper presents a time-delayed model predictive control for power converters used in vehicle to grid and grid to vehicle systems. Finite-based model predictive control has proven to be an alternate digital control method for power converters. However, there are some real-time implementation issues, including specifically time delay, that have to be addressed in order to achieve the system reliability and stability as well as better performance. The proposed method compensates the delay time arising from measuring, calculating, and applying the optimal control sequence in the digital processor. In this way, the delay time is considered in the system input and optimal switching states are applied to the converter once they are available. The proposed method is studied through two benchmarks and verified numerically via MATLAB/Simulink.",
keywords = "delay compensation, electric vehicle, finite-based model predictive control, grid to vehicle, power flow control, prediction horizon, vehicle to grid",
author = "Aghdam, \{Mahlagha Mahdavi\} and Li Li and Jianguo Zhu and Tingting He and Jianwei Zhang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 ; Conference date: 29-10-2017 Through 01-11-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/IECON.2017.8216803",
language = "English",
series = "Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4662--4667",
booktitle = "Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society",
address = "United States",
}