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Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter

Electric vehicles (EVs) are an emerging technology that contribute to reducing air pollution. This paper presents the development of a 200 kW DC charger for the vehicle-to-grid (V2G) application. The bidirectional dual active bridge (DAB) converter was the preferred fit for a high-power DC-DC conver...

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Main Authors: Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Mohd Saad, Norhafidzah, Nur Huda, Ramlan, Bahari, Norhazilina
Format: Article
Language:English
Published: AIMS Press 2023
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/38935/1/AIMS2023_Adaptive%20online%20auto-tuning%20using%20PSO%20optimized%20PI%20controller%20with%20time-variant%20approach%20for%20high%20accuracy%20and%20speed%20in%20dual%20active%20bridge%20converter.pdf
http://umpir.ump.edu.my/id/eprint/38935/
https://doi.org/10.3934/electreng.2023009
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spelling my.ump.umpir.389352023-10-19T06:02:45Z http://umpir.ump.edu.my/id/eprint/38935/ Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter Suliana, Ab Ghani Hamdan, Daniyal Norazila, Jaalam Mohd Saad, Norhafidzah Nur Huda, Ramlan Bahari, Norhazilina TK Electrical engineering. Electronics Nuclear engineering Electric vehicles (EVs) are an emerging technology that contribute to reducing air pollution. This paper presents the development of a 200 kW DC charger for the vehicle-to-grid (V2G) application. The bidirectional dual active bridge (DAB) converter was the preferred fit for a high-power DC-DC conversion due its attractive features such as high power density and bidirectional power flow. A particle swarm optimization (PSO) algorithm was used to online auto-tune the optimal proportional gain (KP) and integral gain (KI) value with minimized error voltage. Then, knowing that the controller with fixed gains have limitation in its response during dynamic change, the PSO was improved to allow re-tuning and update the new KP and KI upon step changes or disturbances through a time-variant approach. The proposed controller, online auto-tuned PI using PSO with re-tuning (OPSO-PI-RT) and one-time (OPSO-PI-OT) execution were compared under desired output voltage step changes and load step changes in terms of steady-state error and dynamic performance. The OPSO-PI-RT method was a superior controller with 98.16% accuracy and faster controller with 85.28 s-1 average speed compared to OPSO-PI-OT using controller hardware-in-the-loop (CHIL) approach. AIMS Press 2023-05-08 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/38935/1/AIMS2023_Adaptive%20online%20auto-tuning%20using%20PSO%20optimized%20PI%20controller%20with%20time-variant%20approach%20for%20high%20accuracy%20and%20speed%20in%20dual%20active%20bridge%20converter.pdf Suliana, Ab Ghani and Hamdan, Daniyal and Norazila, Jaalam and Mohd Saad, Norhafidzah and Nur Huda, Ramlan and Bahari, Norhazilina (2023) Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter. AIMS Electronics and Electrical Engineering, 7 (2). pp. 156-170. ISSN 2578-1588. (Published) https://doi.org/10.3934/electreng.2023009 10.3934/electreng.2023009
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Suliana, Ab Ghani
Hamdan, Daniyal
Norazila, Jaalam
Mohd Saad, Norhafidzah
Nur Huda, Ramlan
Bahari, Norhazilina
Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter
description Electric vehicles (EVs) are an emerging technology that contribute to reducing air pollution. This paper presents the development of a 200 kW DC charger for the vehicle-to-grid (V2G) application. The bidirectional dual active bridge (DAB) converter was the preferred fit for a high-power DC-DC conversion due its attractive features such as high power density and bidirectional power flow. A particle swarm optimization (PSO) algorithm was used to online auto-tune the optimal proportional gain (KP) and integral gain (KI) value with minimized error voltage. Then, knowing that the controller with fixed gains have limitation in its response during dynamic change, the PSO was improved to allow re-tuning and update the new KP and KI upon step changes or disturbances through a time-variant approach. The proposed controller, online auto-tuned PI using PSO with re-tuning (OPSO-PI-RT) and one-time (OPSO-PI-OT) execution were compared under desired output voltage step changes and load step changes in terms of steady-state error and dynamic performance. The OPSO-PI-RT method was a superior controller with 98.16% accuracy and faster controller with 85.28 s-1 average speed compared to OPSO-PI-OT using controller hardware-in-the-loop (CHIL) approach.
format Article
author Suliana, Ab Ghani
Hamdan, Daniyal
Norazila, Jaalam
Mohd Saad, Norhafidzah
Nur Huda, Ramlan
Bahari, Norhazilina
author_facet Suliana, Ab Ghani
Hamdan, Daniyal
Norazila, Jaalam
Mohd Saad, Norhafidzah
Nur Huda, Ramlan
Bahari, Norhazilina
author_sort Suliana, Ab Ghani
title Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter
title_short Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter
title_full Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter
title_fullStr Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter
title_full_unstemmed Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter
title_sort adaptive online auto-tuning using particle swarm optimized pi controller with time-variant approach for high accuracy and speed in dual active bridge converter
publisher AIMS Press
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/38935/1/AIMS2023_Adaptive%20online%20auto-tuning%20using%20PSO%20optimized%20PI%20controller%20with%20time-variant%20approach%20for%20high%20accuracy%20and%20speed%20in%20dual%20active%20bridge%20converter.pdf
http://umpir.ump.edu.my/id/eprint/38935/
https://doi.org/10.3934/electreng.2023009
_version_ 1822923784642887680
score 13.232414

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