Robust energy management system for electric vehicle

The Energy Management System (EMS) is critical for electric vehicle (EV) in order to optimize energy consumption, improve efficiency, and enhance vehicle performance. The EMS provides the optimization of energy distribution among various vehicle components, reduces energy losses and maximizes the ve...

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Main Authors: Challoob A.F., Bin Rahmat N.A., Ramachandaramurthy V.K.A.L., Humaidi A.J.
Other Authors: 58698724700
Format: Article
Published: Akademiai Kiado ZRt. 2025
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spelling my.uniten.dspace-370432025-03-03T15:46:53Z Robust energy management system for electric vehicle Challoob A.F. Bin Rahmat N.A. Ramachandaramurthy V.K.A.L. Humaidi A.J. 58698724700 58698327900 6602912020 57192640171 The Energy Management System (EMS) is critical for electric vehicle (EV) in order to optimize energy consumption, improve efficiency, and enhance vehicle performance. The EMS provides the optimization of energy distribution among various vehicle components, reduces energy losses and maximizes the vehicle's efficacy. The EMS reduces battery stress to prevent excessive charging and discharging cycles; thereby, decreases the necessity for premature battery replacement which, in turn, contributes to the battery's life time. The goal of this research is to develop robust control technique to maximize the use of energy storage systems, renewable energy sources and the bidirectional power flow associated with EVs. The proposed robust control approach is based on combination of flatness theory with artificial neural network. The controller is responsible for maintaining the voltage DC bus stabilized and enhancing the quality of the power fed to the EV side. The performance of controlled EMS is verified via computer simulation within MATLAB/SIMULINK environment. As compared to classical proportional-integral (PI) control, the computer results show the proposed controller (FEMS-ANN) gives higher power quality of EV, lower overshot level in the DC voltage, faster response to abnormal conditions, and less steady state error. ? 2024 The Author(s). Article in press 2025-03-03T07:46:53Z 2025-03-03T07:46:53Z 2024 Article 10.1556/1848.2024.00839 2-s2.0-85204129556 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204129556&doi=10.1556%2f1848.2024.00839&partnerID=40&md5=db43a4dedb72b40d463cf9e8565de9e9 https://irepository.uniten.edu.my/handle/123456789/37043 Akademiai Kiado ZRt. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description The Energy Management System (EMS) is critical for electric vehicle (EV) in order to optimize energy consumption, improve efficiency, and enhance vehicle performance. The EMS provides the optimization of energy distribution among various vehicle components, reduces energy losses and maximizes the vehicle's efficacy. The EMS reduces battery stress to prevent excessive charging and discharging cycles; thereby, decreases the necessity for premature battery replacement which, in turn, contributes to the battery's life time. The goal of this research is to develop robust control technique to maximize the use of energy storage systems, renewable energy sources and the bidirectional power flow associated with EVs. The proposed robust control approach is based on combination of flatness theory with artificial neural network. The controller is responsible for maintaining the voltage DC bus stabilized and enhancing the quality of the power fed to the EV side. The performance of controlled EMS is verified via computer simulation within MATLAB/SIMULINK environment. As compared to classical proportional-integral (PI) control, the computer results show the proposed controller (FEMS-ANN) gives higher power quality of EV, lower overshot level in the DC voltage, faster response to abnormal conditions, and less steady state error. ? 2024 The Author(s).
author2 58698724700
author_facet 58698724700
Challoob A.F.
Bin Rahmat N.A.
Ramachandaramurthy V.K.A.L.
Humaidi A.J.
format Article
author Challoob A.F.
Bin Rahmat N.A.
Ramachandaramurthy V.K.A.L.
Humaidi A.J.
spellingShingle Challoob A.F.
Bin Rahmat N.A.
Ramachandaramurthy V.K.A.L.
Humaidi A.J.
Robust energy management system for electric vehicle
author_sort Challoob A.F.
title Robust energy management system for electric vehicle
title_short Robust energy management system for electric vehicle
title_full Robust energy management system for electric vehicle
title_fullStr Robust energy management system for electric vehicle
title_full_unstemmed Robust energy management system for electric vehicle
title_sort robust energy management system for electric vehicle
publisher Akademiai Kiado ZRt.
publishDate 2025
_version_ 1825816040967241728
score 13.244109