@inbook{2b3f3ad70b074f75bad7cbff8c9f719c,
title = "An Improved Kalman Filter-Based Model Predictive Control for Dual Active Bridge Converter",
abstract = "The Dual Active Bridge (DAB) converter is a versatile bidirectional DC/DC converter that is essential for facilitating bidirectional energy flow in electric vehicle charging systems. This article presents a comprehensive analysis of the performance and efficiency of a DAB converter designed for electric vehicle (EV) charging stations. A modified Kalman filter-based model predictive control (KF-MPC) is proposed to ensure that the DAB converter operates under both soft switching and minimum current stress conditions during the bidirectional power flow. The effectiveness of the proposed KF-MPC is demonstrated, showcasing its robust tracking and adaptive capabilities. Additionally, the article examines the efficiency and power loss characteristics of the DAB converter across a range of power ratings. The proposed control method is validated and analysed in a MATLAB-based simulation environment. These insights are critical for developing efficient and reliable EV charging infrastructure, supporting the broader adoption of EVs and contributing to sustainable transportation solutions.",
keywords = "DAB Efficiency, Dual Active Bridge, EV Charging Station, Kalman Filter, Model Predictive Control, State-Space Modelling",
author = "Sandipan Patra and Mohamed Shadnam and Shafi Khadem",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2024 ; Conference date: 10-10-2024 Through 12-10-2024",
year = "2024",
doi = "10.1109/ICAIGE62696.2024.10776714",
language = "English",
series = "2024 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2024",
address = "United States",
}
