Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Robotics and Automation (IJRA) International Journal of Applied Power Engineering (IJAPE) International Journal of Advances in Applied Sciences
Kalagotla Chenchireddy
Geethanjali College of Engineering and Technology
Automotive Engineering Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Intelligent control strategies for grid-connected photovoltaic wind hybrid energy systems using ANFIS Thiruveedula Madhu Babu; Kalagotla Chenchireddy; Kotha Kalyan Kumar; Vasukul Nehal; Sappidi Srihitha; Marikal Ram Vikas
International Journal of Advances in Applied Sciences Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i3.pp497-506

Abstract

This study proposes intelligent control strategies for optimizing the grid integration of photovoltaic (PV) and wind energy in hybrid systems using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS control aims to enhance grid stability, improve power management, and maximize renewable energy (RE) utilization. The hybrid system's performance is evaluated through simulations, considering various environmental conditions and load demands. Results demonstrate the effectiveness of the proposed ANFIS-based control in dynamically adjusting the power output from PV and wind sources, ensuring efficient grid-connected operation. The findings underscore the potential of intelligent control strategies to contribute to the reliable and sustainable integration of RE into the grid.
Photovoltaic-inductive wireless charging for electric vehicles Azra Zaineb; P. Nagabushanam; Kalagotla Chenchireddy; Radhika Dora; Naresh Jella; Shabbier Ahmed Sydu
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i2.pp849-857

Abstract

The growing demand for electric vehicles (EVs) necessitates efficient and eco-friendly charging methods. This study presents a photovoltaic-inductive wireless charging (PIWC) system, which integrates solar energy harvesting with inductive power transfer (IPT) to enable seamless operation without physical connectors. The system utilizes solar photovoltaic (PV) panels to generate renewable energy, which is then converted and transmitted wirelessly using resonant inductive coupling. This eliminates the need for physical connections, reducing wear and maintenance while supporting both stationary and dynamic charging applications. To enhance performance, maximum power point tracking (MPPT) controllers optimize solar energy utilization. Power electronics and control strategies regulate the energy transfer, ensuring efficient and stable operation. Additionally, IoT-based monitoring enables real-time system analysis and performance tracking. Through simulations and prototype evaluations, the system's feasibility, efficiency, and environmental impact are assessed. Results indicate that PIWC can minimize grid dependency, providing a sustainable, autonomous, and convenient charging solution for EVs. This innovation contributes to cleaner transportation and the advancement of renewable energy-driven mobility.
High risk industries for advanced lightning protection system Kalagotla Chenchireddy; P. Nagabushanam; Radhika Dora; Vadthya Jagan; Shabbier Ahmed Sydu; Nunavath Praveen
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i2.pp958-965

Abstract

Lightning strikes are a serious risk for high-risk facilities like oil and gas plants, mines, explosive storage, and data centers. These places hold the sensitive equipment and dangerous materials, and a lightning strike can cause major damage, leading to expensive downtime or even disastrous events such as fires or explosions. That’s why having a strong lightning protection system is not just a matter of following rules, but it is crucial for protecting both people and property. The complete lightning protection solutions designed to meet the specific needs of these critical industries. The services include lightning simulations and both isolated and attached lightning protection systems. This study investigates the real-time installation and testing of advanced lightning protection systems across high-risk industries like oil and gas plants, mines, explosive storage, and data centers. This ensures that the facility stays safe and continues to operate, even during severe weather. By investing in an effective lightning protection system, you can help secure your assets and keep everyone safe, focusing on what really matters in your industry.
Intelligent gear shifting in electric and hybrid vehicles: a CAN controller-based approach using SOC% Kalagotla Chenchireddy; Naresh Jella; Vadthya Jagan; R. Naveena Bhargavi; Shabbier Ahmed Sydu; Nunavath Praveen
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp581-589

Abstract

The intelligent management of gear shifting in electric and hybrid vehicles (EVs and HEVs) is essential for optimizing energy efficiency, improving fuel economy, and enhancing driving comfort. Traditional gear shifting strategies, which are designed for internal combustion engine (ICE) vehicles, do not fully accommodate the unique dynamics of electric and hybrid powertrains. This paper proposes a novel approach for gear shifting in EVs and HEVs, integrating the state of charge (SOC%) of the battery as a critical input for decision-making. The proposed algorithm utilizes real-time data from the vehicle's controller area network (CAN), enabling seamless communication between the transmission control unit, battery management system, and powertrain control module. The algorithm adjusts gear shifting based on SOC%, vehicle speed, engine RPM, and throttle position, ensuring optimal use of the electric motor and internal combustion engine. At high SOC%, the algorithm prioritizes electric motor use to conserve fuel and extend battery life, while at lower SOC%, it switches to relying more on the combustion engine. The proposed method optimizes energy usage, enhances fuel efficiency, and prolongs battery life by adapting the shifting strategy to varying driving conditions.
River cleaning robot using Arduino microcontroller Dubala Ramadevi; Kalagotla Chenchireddy; Barkam Rekha; Sunkari Prathyusha; Koriginja Shravani; Karnati Bhargavi
IAES International Journal of Robotics and Automation (IJRA) 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/ijra.v14i3.pp332-338

Abstract

River cleaning robots represent a promising technological solution to address the pervasive issue of water pollution in river systems. These autonomous devices are designed to collect and remove various types of debris from river environments, contributing to improved water quality and ecosystem health. This abstract summarizes the key aspects of river cleaning robots, including their technological advancements, operational mechanisms, and environmental impact. River cleaning robots have evolved significantly from early mechanical designs to sophisticated autonomous systems. Initially, these robots were equipped with basic skimming and collection mechanisms. Recent advancements have incorporated state-of-the-art technologies, including artificial intelligence, machine learning, and advanced sensor systems. Modern river cleaning robots can autonomously navigate complex river environments, detect and classify different types of debris, and operate efficiently with minimal human intervention. The operational capabilities of these robots are enhanced by various design features such as mobility systems, debris collection mechanisms, and renewable power sources. Mobility systems allow robots to maneuver through diverse water conditions, while collection mechanisms like nets, scoops, and suction devices enable effective debris removal. Many robots are powered by renewable energy sources, such as solar panels, which contribute to their sustainability and reduce their environmental footprint.
Co-Authors Azra Zaineb Barkam Rekha Dubala Ramadevi Karnati Bhargavi Koriginja Shravani Kotha Kalyan Kumar Marikal Ram Vikas Naresh Jella Nunavath Praveen P. Nagabushanam P. Nagabushanam R. Naveena Bhargavi Radhika Dora Sappidi Srihitha Shabbier Ahmed Sydu Shabbier Ahmed Sydu Sunkari Prathyusha Thiruveedula Madhu Babu Vadthya Jagan Vasukul Nehal