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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE)
Panigrahi, Chinmoy Kumar
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Control & Systems Engineering Electrical & Electronics Engineering

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A new GaN-based converter design for electric vehicle charging system Snehalika, Snehalika; Patel, Ranjeeta; Abhishek, Amruta; Panigrahi, Chinmoy Kumar; Pati, Ranjan Keshari
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1594-1608

Abstract

The research work proposes a gallium nitride (GaN) based isolated bidirectional DC-DC (IBDC)-triple active bridge (TAB) based multi-port converter (MPC) for electric vehicle (EV) charging. The proposed GaN IBDC-TAB based MPC incorporates one input port (Port 1) and two output ports (Port 2 and Port 3) for charging, implying the use of fewer components compared to a conventional dual active bridge (DAB) charging system. The output ports can be operated individually in single active bridge (SAB), Dual active bridge (DAB), and TAB modes. A 12 kW GaN IBDC-TAB based MPC converter is designed for simulation study using LTspice XVII software. In the TAB mode of operation, output Port 2 designated for Level-1 (L-1) charging produces 1.5 kW, and output Port 3 designated for Level-2 (L-2) charging produces 10.6 kW. The maximum efficiency of 98.87% is obtained in simulation for the MPC converter in TAB mode. For experimental validation, a 0.91 kW prototype is presented with Port 1, Port 2, and Port 3 voltages as 230 V, 120 V, and 200 V respectively with the considered switching frequency of 100 kHz. The single-phase-shift control strategy is implemented for controlling the transmitted power in the proposed GaN IBDC-TAB converter.
AI-driven solutions for Li-ion battery performance and prediction Mishra, Sthitprajna; Panigrahi, Chinmoy Kumar; Debdas, Subhra; Bandyopadhyay, Atri; Velpula, Srikanth; Sahoo, Amit Kumar; Tripathy, Pabitra Kumar
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i3.pp569-578

Abstract

Batteries serve as crucial power sources for essential portable devices like electric vehicles, smartphones, and laptops. The widespread adoption of Li-ion batteries, while beneficial, has unfortunately led to a surge in adverse incidents. The sudden failure of batteries in both industrial and lightweight applications poses significant economic risks across various industries. Consequently, researchers are intensifying their focus on enhancing battery state estimation, management systems, and predicting remaining useful life (RUL). This paper is structured into three main sections. Firstly, it delves into the acquisition of battery data, encompassing both commercially available and freely accessible Li-ion battery datasets. Secondly, the exploration extends to techniques for estimating battery states through advanced battery management systems. The paper investigates battery RUL estimation, categorizing and evaluating diverse prognostic methods applied to Li-ion batteries based on crucial performance parameters. The review includes scrutiny of commercially and publicly available datasets for various battery models and conditions, considering different battery states and the role of advanced battery management system (BMS). In the final section, the paper concludes with a comparative analysis of Li-ion battery RUL prediction, incorporating exploration into various RUL prediction algorithms, and mathematical models, and introducing an AI-based cloud monitoring system.
Dual-aware EV charging scheduling with traffic integration Yadav, Maneesh; Jena, Satyaranjan; Panigrahi, Chinmoy Kumar; Pati, Ranjan Keshari; Sahu, Jayanta Kumar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1446-1456

Abstract

Electric vehicle adoption is a trend in many countries, and the demand for charging station infrastructure is at a rapid pace. The placement of charging stations is the key research topic of many researchers, but charging scheduling is also a problem that is going to rise in the near future. The proper charger utilization, maintaining coordination between charging stations, and satisfying users' demands are some of the key challenges. The traffic pattern is uncertain, coordination of distances between charging stations and users is done by Euclidean distance. The traffic-aware fair charging scheduling (TAFCS) strategy is proposed, which will have a balance on charger utilization and user prioritization, and keep the fairness by equal distribution of electric vehicles among all the charging stations having a centralized charging system monitored by an aggregator. The distribution of the traffic pattern of electric vehicles is performed by Monte Carlo simulation. The proposed system is tested on the IEEE 33 bus standard system using the predefined voltage limits of each bus and limiting power loss to lessen its burden. The discharging process of 50 electric vehicles (V2G) is performed by optimal placement by obtaining the weakest buses, which makes it an intelligent distribution system. This proposed charging framework is validated on MATLAB R2020a.
Co-Authors Abhishek, Amruta Bandyopadhyay, Atri Debdas, Subhra Jena, Satyaranjan Mishra, Sthitprajna Patel, Ranjeeta Pati, Ranjan Keshari Sahoo, Amit Kumar Sahu, Jayanta Kumar Snehalika, Snehalika Tripathy, Pabitra Kumar Velpula, Srikanth Yadav, Maneesh