Modeling and Performance Evaluation of ANFIS Controller-Based Bidirectional Power Management Scheme in Plug-In Electric Vehicles Integrated With Electric Grid

Md. Ariful Islam; Jai Govind Singh; Israt Jahan; M. S. Hossain Lipu; Taskin Jamal; Rajvikram Madurai Elavarasan; Lucian Mihet-Popa

doi:10.1109/ACCESS.2021.3135190

IEEE Access (Jan 2021)

Modeling and Performance Evaluation of ANFIS Controller-Based Bidirectional Power Management Scheme in Plug-In Electric Vehicles Integrated With Electric Grid

Md. Ariful Islam,
Jai Govind Singh,
Israt Jahan,
M. S. Hossain Lipu,
Taskin Jamal,
Rajvikram Madurai Elavarasan,
Lucian Mihet-Popa

Affiliations

Md. Ariful Islam: ORCiD; Department of Electrical and Electronic Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh
Jai Govind Singh: ORCiD; Department of Energy, Environment, and Climate Change, School of Environment, Resources and Development, Asian Institute of Technology (AIT), Khlong Nueng, Pathum Thani, Thailand
Israt Jahan: Department of Electrical and Electronic Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh
M. S. Hossain Lipu: ORCiD; Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
Taskin Jamal: ORCiD; Department of Electrical and Electronic Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh
Rajvikram Madurai Elavarasan: ORCiD; Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, India
Lucian Mihet-Popa: ORCiD; Faculty of Electrical Engineering, Østfold University College, Halden, Norway

DOI: https://doi.org/10.1109/ACCESS.2021.3135190
Journal volume & issue: Vol. 9
pp. 166762 – 166780

Abstract

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A bi-directional power exchange between the plug-in electric vehicle (PEV) and the AC electrical grid is necessary to perform the Vehicle to Grid (V2G) and Grid to Vehicle (G2V) operations. While performing these operations, different power converters and controllers play an important role as mediators between the PEV and electric grid. Various works have demonstrated the utilization of controllers for PEV’s battery power management. However, the existing conventional controllers have technical shortcomings about vulnerability to controller gain, accurate mathematical modelling, poor adaptability, sluggish response to a sudden outburst and lengthy interval execution processing. Therefore, this paper develops an adaptive neuro-fuzzy inference system (ANFIS) control strategy based bidirectional power management scheme to ensure the optimal electrical power flow exchange between the AC electrical grid and battery storage system in PEVs. This paper aims to reduce the stress on the grid power side and utilize the unused power properly. The performance of the ANFIS model is varied using two PEVs based on real-life power consumptions by different loads at home based on five operational modes. Besides, a comparative analysis between the ANFIS controller and the PI controller is carried out to demonstrate the effectiveness of the proposed control scheme. The results illustrate that the proposed ANFIS controller delivers a smoother power injection from the PEV to the AC power grid with the least harmonics as well as achieves a smoother battery profile and less distortion when power is absorbed by PEV battery.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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