Model Predictive Control for Dual Active Bridge in fast Charging Application of Electric Vehicles

Mohamed Elkeiy, Ralph Kennel, Ayman Abdel-Khalik, Mohamed Abdelrahem

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

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.

OriginalspracheEnglisch
Titel2022 23rd International Middle East Power Systems Conference, MEPCON 2022
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9781665463638
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung23rd International Middle East Power Systems Conference, MEPCON 2022 - Cairo, Ägypten
Dauer: 13 Dez. 202215 Dez. 2022

Publikationsreihe

Name2022 23rd International Middle East Power Systems Conference, MEPCON 2022

Konferenz

Konferenz23rd International Middle East Power Systems Conference, MEPCON 2022
Land/GebietÄgypten
OrtCairo
Zeitraum13/12/2215/12/22

Fingerprint

Untersuchen Sie die Forschungsthemen von „Model Predictive Control for Dual Active Bridge in fast Charging Application of Electric Vehicles“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren