Dr. Raman Manivannan
SASTRA University, Chonbuk National University, Thiruvalluvar University, National Institute of Technology Calicut, Bharathiar University
0000-0003-4212-1305
About
R. Manivannan received the B.Sc. degree in mathematics from Sacred Heart College (Autonomous), Tirupattur, India, in 2009, the post-graduation degree in mathematics from Islamiah Men’s College (Autonomous), Vaniyambadi, India, in 2012, the M.Phil. degree in mathematics with a specialization in numerical studies on fluid dynamics from Bharathiar University, Coimbatore, India, in 2014, and the Ph.D. degree in mathematics with a specialization in dynamical behaviors of generalized delayed neural networks from Thiruvalluvar University, Vellore, India, in 2017. He was a Junior Research Fellow and a Senior Research Fellow with the Department of Science and Technology-Science and Engineering Research Board, Government of India, New Delhi, India, from 2014 to 2016. He was an Adhoc Assistant Professor with the Department of Mathematics, School of Natural Sciences, National Institute of Technology Calicut, Kozhikode, India, from August 2017 to January 2018. He was a Post-Doctoral Research Fellow and Hope-IT Post-Doctoral Research Fellow with the Advanced Research Center of Electronics and Information, Division of Electronic Engineering, Chonbuk National University, Jeonju, South Korea, from January 2018 to February 2019. He was an Assistant Professor with the Department of Mathematics at SASTRA Deemed University, Thanjavur, India, from December 2019 to May 2026. During his tenure, he established the Artificial Intelligence, Energy, and Control Systems (AIE & CS) Laboratory through an ANRF Core Research Grant (CRG)-funded project, equipping it with advanced lithium-ion battery testing facilities. The laboratory focuses on advanced battery modeling, real-time data acquisition, intelligent energy management, and robust state estimation techniques for electric vehicle (EV) applications.
He served as the Principal Investigator of an ANRF-CRG-funded research project on the estimation of the State of Charge (SOC) and State of Health (SOH) of lithium-ion batteries for electric vehicles using hybrid Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) approaches integrated with advanced observer design and filtering techniques. He is currently an Associate Professor Grade 1 in the Department of Mathematics, School of Advanced Sciences (SAS), Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, India. His research focuses on the development of robust, adaptive, and computationally efficient algorithms for battery management systems operating under varying temperature and dynamic operating conditions. He has authored more than 40 SCI/SCIE-indexed journal articles in reputed international journals with high impact factors. His research interests include battery modeling and diagnostics, battery health management systems, nonlinear state estimation, electric vehicles, neural networks, artificial intelligence, Kalman filtering techniques, robust control theory, and extended dissipativity analysis.
Dr. Manivannan serves as an active reviewer for various SCI journals, including the IEEE Transactions.
Employment
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SASTRA University Assistant Professor - II2019 - 2026
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Chonbuk National University Hope-IT Post Doc Researcher2018 - 2019
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Chonbuk National University Post-doctoral Research Fellow2018 - 2019
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National Institute of Technology Calicut Adhoc Assistant Professor2017 - 2018
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Thiruvalluvar University Senior Research Fellow2016 - 2017
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Thiruvalluvar University Junior Research Fellow2014 - 2016
Education
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Chonbuk National University Post-doctoral Research Fellow2018 - 2019
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Thiruvalluvar University Ph.D.,2014 - 2016
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Bharathiar University M.Phil.,2012 - 2013
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Islamiah College M.Sc.,2010 - 2012
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Sacred Heart College B.Sc.,2006 - 2009
Projects & Funding
Projects & funding information is unavailable.
Publications (41)
- A Multi-Head Attention ResCNN–BiGRU Model for Robust SOC Estimation in EVs Lithium-Ion Batteries Using Real-World Driving Data Save
- A Novel Approach for Accurate SOC Estimation of Lithium-Ion Electric Vehicle Batteries Using a (Q, S, R)-$γ$-Based Dissipativity Observer Save
- An Improved Robust H∞ Observer Framework for State-of-Charge Estimation of Lithium-Ion Batteries in Electric Vehicles Save
- A Novel Data-Driven Machine Learning Framework for SOC Estimation in EV Batteries: A White-Box Approach Using Elastic Net Regression Save
- A Novel Dissipativity-Based Observer for State of Charge Estimation in Lithium-Ion Electric Vehicle Batteries: An Experimental Approach Save
- Mathematical Modeling and Experimental Approach for State of Charge Estimation in Samsung 30Q Li-Ion Batteries using a Passivity Observer Save
- State-of-Charge Estimation for EV Li-Ion Batteries using ResNet: A Robust Deep Learning Approach with Real-World Driving Data Save
- A comprehensive review of fractional-order mathematical models for lithium-ion batteries: Historical progress, recent advancements, and future outlooks Save
- Experimental Design and Mathematical Modeling of $A$123 Li-ion EV Pouch Cell for the State of Charge Estimation via Dissipativity Observer Save
- Generalized state estimation criteria for additive delayed memristor neural networks including leakage delay effect-flux-charge domain applications in energy storage systems Save