Suliana, Ab Ghani and Hamdan, Daniyal and Norazila, Jaalam and Norhafidzah, Mohd Saad and Nur Huda, Ramlan (2022) Dynamic control and performance of dual active bridge converter based particle swarm optimization. In: IET Conference Proceedings. 2022 Engineering Technology International Conference, ETIC 2022 , 7 - 8 September 2022 , Kuantan, Virtual. pp. 312-316., 2022 (22). ISSN 2732-4494 ISBN 978-183953782-0 (Published)
Pdf
Dynamic control and performance of dual active bridge.pdf Restricted to Repository staff only Download (518kB) | Request a copy |
||
|
Pdf
Dynamic control and performance of dual active bridge converter based particle swarm optimization_ABS.pdf Download (106kB) | Preview |
Abstract
This paper presents analysis of the dynamic response of the isolated bidirectional dual active bridge (DAB) DC-DC converter using particle swarm optimization (PSO) algorithm. On the basis, the fast dynamic response is one of the main control objective for DAB system to ensure the system able to have fast time recovery and adapt with various control environment. A 200 kW DAB system with single-phase shift (SPS) modulation is tested for direct and indirect online tuning phase-shift angle, ϕ using PSO algorithm. In direct tuning, the optimal ϕ is directly tuning using PSO. While in indirect tuning method, the optimal values of PI parameters are functioning to well-tuned the desired ϕ in the DAB system, where both values of KP and KI have been optimized using the PSO algorithm. The DAB performance with both proposed methods is evaluated in terms of dynamic response for load step changes under various reference voltages. Comparative analysis between direct and indirect methods are carried out using hardware in-the-loop (HIL) experimental. The DAB with indirect online tuning produces 11.50ms faster response compared to the direct online tuning method.
Item Type: | Conference or Workshop Item (Lecture) |
---|---|
Additional Information: | Indexed by Scopus |
Uncontrolled Keywords: | Dual active bridge; High dynamic response; Online tuning; Particle swarm optimization |
Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Faculty/Division: | Faculty of Electrical and Electronic Engineering Technology |
Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
Date Deposited: | 30 Sep 2024 04:42 |
Last Modified: | 30 Sep 2024 04:42 |
URI: | http://umpir.ump.edu.my/id/eprint/42066 |
Download Statistic: | View Download Statistics |
Actions (login required)
View Item |