Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)

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A Novel ANFIS with the Optimized FOPID Controller-Based Multi-Objective Metaheuristic Algorithm-Based Efficient Regenerative Control System for EV Charging

Authors
C. Subathradevi1, *, S. Prakash1
1Eelectrical and Electronics Engineering, Bharath Institute of Higher Education and Research, Tambaram, Chennai, Tamilnadu, India
*Corresponding author. Email: csubathradevi8@gmail.com
Corresponding Author
C. Subathradevi
Available Online 24 April 2026.
DOI
10.2991/978-94-6239-654-8_8How to use a DOI?
Keywords
ANFIS; FOPID; Energy Management System; HBA
Abstract

The rapid proliferation of electric vehicles (EVs) has created an urgent need for intelligent and adaptive energy management systems, especially for optimizing regenerative braking and charging efficiency. Conventional control strategies, such as classical PID Controllers, often exhibit limitations in handling system nonlinearity, parameter variations, and multi-objective performance trade-offs, leading to energy inefficiencies and reduced battery lifespan. To overcome these challenges, this paper proposes a novel hybrid control strategy that integrates an Adaptive Neuro-Fuzzy Inference System (ANFIS) and a Fractional-Order PID (FOPID) controller, optimized using the Self-Adaptive Honey Badger Algorithm (SA-HBA). The proposed control scheme integrates a DC-DC Buck-Boost converter to manage energy flow between the EV battery and regenerative braking system. The developed control framework dynamically adjusts key parameters in real time to Additionally, the controller demonstrates strong robustness under varying load conditions and road profiles, indicating its demonstrates strong robustness under varying load conditions and road profiles, indicating its suitability for implementation in advanced EV charging systems.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
Series
Advances in Engineering Research
Publication Date
24 April 2026
ISBN
978-94-6239-654-8
ISSN
2352-5401
DOI
10.2991/978-94-6239-654-8_8How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - C. Subathradevi
AU  - S. Prakash
PY  - 2026
DA  - 2026/04/24
TI  - A Novel ANFIS with the Optimized FOPID Controller-Based Multi-Objective Metaheuristic Algorithm-Based Efficient Regenerative Control System for EV Charging
BT  - Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
PB  - Atlantis Press
SP  - 79
EP  - 95
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-654-8_8
DO  - 10.2991/978-94-6239-654-8_8
ID  - Subathradevi2026
ER  -