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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) International Journal of Applied Power Engineering (IJAPE) Bulletin of Electrical Engineering and Informatics
Rajanna, Bodapati Venkata
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Solar and battery input super boost DC–DC converter for solar powered electric vehicle Yadagiri, Aerpula; Talagadadeevi, Srinivasa Rao; Rao, Seetamraju Venkata Bala Subrahmanyeswara; Rao, Bitra Janardhana; Inthiyaz, Syed; Prakash, Nelaturi Nanda; Rajanna, Bodapati Venkata; Kumar, Cheeli Ashok
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i2.pp479-487

Abstract

The electric vehicle (EV) is increasingly emerging as an attractive solution to reduce reliance on fossil fuels in India. In commercial EVs, solar photovoltaic (PV) technology is employed both to charge the battery and power the vehicle. However, the conventional bidirectional DC-DC converter layout results in underutilization of solar PV power when the battery's state of charge (SOC) reaches maximum capacity. This work offers a unique dual input super boost (DISB) DC-DC converter designed specifically for solar-powered electric vehicles (EVs) to address the aforementioned challenge. The recently suggested converter operates in six different modes to effectively capture solar photovoltaic (PV) power. Notable benefits of this design include a wide range of speed control and fewer conduction devices in each mode, which eventually result in increased overall efficiency. An extensive analysis of the suggested DISB DC-DC converter is carried out by the study, encompassing detailed examination of operating waveforms and dynamic evaluations. Furthermore, the converter's performance and operation under the six different modes are verified through simulation.
Power quality enhancement for a grid connected wind turbine energy system with PMSG Rajasri, Kasula; Kiranbabu, Movva Naga Venkata; Raja, Banda Srinivas; Parvez, Muzammil; Reddy, Govulla Ravi Kumar; Prakash, Nelaturi Nanda; Ahammad, Sk. Hasane; Rajanna, Bodapati Venkata
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i2.pp392-400

Abstract

This project investigates the burgeoning potential of gearless wind turbine systems as a pivotal clean energy resource. Unlike conventional gearbox-based turbines, which grapple with issues like frequent breakdowns, intricate repairs, and prolonged downtimes, gearless systems present a suite of advantages. Chief among these is heightened reliability, diminished maintenance costs, and augmented efficiency. By circumventing the need for a gearbox, gearless turbines shed weight, bolster reliability, and demand less upkeep. The incorporation of permanent magnet generators further elevates their efficiency and renders them well-suited for offshore deployment. The emergence of gearless wind turbines heralds a promising frontier for effectively and efficiently harnessing wind power. Their streamlined design and robust performance potential position them as a transformative force in the renewable energy landscape, poised to catalyze substantial advancements towards sustainable energy goals. As research delves deeper into their capabilities and optimization, gearless turbines are poised to emerge as a cornerstone technology in the global pursuit of clean energy solutions.
Design and development of AC motor speed controlling system using touch screen with over heat protection Rani, Prathipati Ratna Sudha; Eragamreddy, Gouthami; Inthiyaz, Syed; Ravikanth, Sivangi; Najumunnisa, Mohammad; Rajanna, Bodapati Venkata; Kumar, Cheeli Ashok; Ahammad, Shaik Hasane
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2429-2440

Abstract

Design and implementation of an AC motor speed control and monitoring system based on a touch screen interface with built-in overheat protection, utilizing Arduino, meets the increasing demand for efficient, user-friendly motor control in many industrial applications. This system offers an easy-to-use interface to manage the speed of an AC motor, with real-time feedback and adjustments through a touch screen display. The system employs an Arduino microcontroller, which accepts inputs from the touch screen and processes these to regulate the motor's speed through a pulse width modulation (PWM) method. The system also has an overheat protection system, which it is able to monitor the temperature of the motor via a temperature sensor. When the motor reaches a predetermined temperature, the system automatically shuts off power to avoid damage. The intuitive touch screen facilitates convenient monitoring of motor parameters like temperature, giving a smooth experience to operators. The modular design of the system provides scalability across applications, ranging from household appliances to large industrial systems, with reliability, energy efficiency, and safety in motor-driven processes.
Bidirectional power converter for electrical vehicle with battery charging and smart battery management system Rajanna, Bodapati Venkata; Krishnaiah, Kondragunta Rama; Reddy, Ganta Raghotham; Ahammad, Shaik Hasane; Najumunnisa, Mohammad; Inthiyaz, Syed; Eragamreddy, Gouthami; Sudhakar, Ambarapu; Kolukula, Nitalaksheswara Rao
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2592-2604

Abstract

In electric vehicles (EVs), efficient energy management is critical for reliable power transfer between the battery and motor. This paper presents the design and implementation of a bidirectional DC-DC converter equipped with a smart battery management system (BMS). The system supports bidirectional power flow, operating in boost mode during acceleration and buck mode during regenerative braking, thereby enhancing overall energy efficiency and vehicle performance. A PIC microcontroller governs the system, performing real-time monitoring of key battery parameters such as state of charge (SOC), state of health (SOH), voltage, and temperature. Safety features include automatic cooling fan activation when the temperature exceeds 45 °C and generator startup when battery voltage falls below 23 V. Real-time data is displayed via an LCD interface to improve user interaction and system transparency. The proposed system achieved a conversion efficiency of 90-93% during experimental testing, with stable switching, reliable automation, and effective thermal protection. The embedded energy management system optimizes charging and discharging cycles while preventing overcharging, deep discharge, and thermal stress. This intelligent, automated power converter enhances battery life, improves EV reliability, and contributes to sustainable transportation by enabling features like vehicle-to-grid (V2G) energy transfer. The proposed architecture is well-suited for integration into modern EV infrastructure. Although the system architecture supports future V2G integration, V2G functionality was not implemented or tested in the present experimental setup.
Brain tumor classification using PCA-NGIST features with an enhanced RELM classifier Babu, Bukkapatnam Rakesh; Rajesh, Vullanki; Rajanna, Bodapati Venkata; Ahammad, Shaik Hasane
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10742

Abstract

Brain tumours may cause severe health risks because of abnormal cell growth, which may result in organ malfunctions and death in adulthood. As precise identification of the tumour type is required for effective treatment. Magnetic resonance imaging (MRI) has recently been provided as an effective method for brain tumour diagnosis by computer-based based systems. To categorize brain tumours from MRI images, the paper offered a fusion model integrating an enhanced regularized extreme learning machine (RELM) classifier with principal component analysis (PCA) and normalized GIST (NGIST) feature extraction. While NGIST extracts strong spatial and texture features essential for modelling the tumour, PCA reduces the dimension of the input features without sacrificing significant data patterns. The improved RELM efficiently categorizes brain tumours into three categories: pituitary, meningioma, and glioma. It is optimized to improve learning capacity and generalization. The novelty of this study lies in the integration of NGIST descriptors with PCA-driven dimensionality reduction and an enhanced RELM classifier in a single lightweight framework. Unlike conventional methods that trade accuracy for computational cost, the proposed model ensures high precision and recall while remaining computationally efficient. This unique fusion demonstrates significant improvements in both diagnostic accuracy of 96% and clinical applicability, offering a balanced solution for real-time brain tumor classification.
Co-Authors Ahammad, Shaik Hasane Ahammad, Sk. Hasane Babu, Bukkapatnam Rakesh Balaswamy, Chinthaguntla Batakala, Jeevanrao Bhavana, Mukku Chaturvedi, Abhay Cheerla, Sreevardhan Daniel, Ravuri Eamani, Ramakrishna Reddy Eragamreddy, Gouthami Himabindu, D. Inthiyaz, Syed Kallakunta, Ravi Kumar Kallakuta, Ravi Kumar Kameswari, Yeluripati Lalitha Karthik, Nachagari Kiranbabu, Movva Naga Venkata Kolukula, Nitalaksheswara Rao Krishnaiah, Kondragunta Rama Kumar, Cheeli Ashok Kumar, Mugachintala Dilip Kumar, Munuswamy Siva Kumar, Yarrem Narasimhulu Vijaya Kumari, Popuri Rajani Mohan, Kaja Krishna Mohana, Thota Naidu, Madhireddi Bhaskara Najumunnisa, Mohammad Nandaprakash, Nelaturi Parvez, Muzammil Pasam, Prudhvi Kiran Prakash, Nelaturi Nanda Prasad, Bode Raja, Banda Srinivas Rajasri, Kasula Rajesh, Vullanki Ramu, Tirunagari Bhargava Rani, Prathipati Ratna Sudha Rao, Bitra Janardhana Rao, Seetamraju Venkata Bala Subrahmanyeswara Ravikanth, Sivangi Reddy, Ganta Raghotham Reddy, Govulla Ravi Kumar Reddy, Mula Sreenivasa Reddy, Tadi Diwakara Subba Sai, Cheepurupalli Krishna Chaitanya Shashank, Ramagiri Sudarsa, Dorababu Sudhakar, Ambarapu Surendher, Guntukala Talagadadeevi, Srinivasa Rao Vinodhkumar, Nallathambi Yadagiri, Aerpula