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All Journal International Journal of Applied Power Engineering (IJAPE) International Journal of Advances in Applied Sciences
Babu, Thiruveedula Madhu
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Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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High voltage DC-DC converter with standalone application Babu, Thiruveedula Madhu; Chenchireddy, Kalagotla; Rohini, Jakkani; Suhas, Mesaragandla Sai; Ajitesh, Dara; Rahul, Kanaparthi
International Journal of Applied Power Engineering (IJAPE) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v12.i4.pp384-390

Abstract

Designing DC-DC converters involves many voltage lift techniques. These techniques have been encouraged for their credible advantages. Most voltage lifting methods are applied in many areas of automotive, motor drives, telecom and electronic welfare in military applications. Voltage lifting techniques are known for their high voltage transfer gain and high efficiency. Ultra-lift converter yields very high output transfer gain with geometric progression compared to other voltage lift techniques such as super lift converters and classical boost converters. It also offers reduced size and improved efficiency when compared. In this proposed method ultra-lift converter operation is analyzed with continuous conduction mode.
An innovative design and development of multilevel inverter for a wind energy conversion system Mudigondla, Rosaiah; Babu, Thiruveedula Madhu; Dachepalli, Supriya; Panjula, Anudeep; Ali, Md Yousuf; Anirudh, Bakam
International Journal of Advances in Applied Sciences 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/ijaas.v14.i3.pp751-760

Abstract

The drawbacks of fossil fuel-based energy sources, including high costs, pollution, scarcity, and environmental damage, highlight how urgent it is to switch to renewable energy sources. Multilevel inverters (MLIs) are currently required for the production of wind electricity. In this research, to get a reduced harmonic distortion, use 31-level inverter based on shifted carrier-pulse width modulation (SC-PWM) is developed for wind power generation using MATLAB/Simulink. It aids in minimizing the total harmonic distortion (THD) to 3.20, and the output voltage is enhanced by the suggested MLI. Wind energy extraction is optimized by combining with a proportional integral derivative (PID) control system. MATLAB/Simulink has been used to make sure the MLI structure and look into the implementation of wind energy conversion systems using a permanent magnet synchronous generator (PMSG). In order to show that the suggested inverter architecture improves power conversion efficiency and stability in renewable energy systems, the study also examines power efficiency, system dependability, and the viability of large-scale applications. Additionally, the study investigates grid integration, modulation strategies, and switching losses to guarantee increased sustainability, dependability, and efficiency in wind energy applications while lowering operating costs.
Artificial neural network based sensorless position estimation and direct torque control for stepper motor Arise, Nagasridhar; Babu, Thiruveedula Madhu; Gollapudi, Srinidhi; Dommeti, Tarun Kumar; Kummari, Abhishek; Shambukari, Mahith
International Journal of Advances in Applied Sciences 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/ijaas.v14.i3.pp702-710

Abstract

This study describes and illustrates how sensorless location estimation is achieved through the application of artificial neural network (ANN) control. Control stepper motor torque directly. Using stepper motors directly leads to a lot of problems; therefore, automated control systems are now commonly preferred. Stepper motors have several drawbacks when used directly, including the potential for steps to occasionally be missing while the motors are running. When physical sensors are not available, the proposed method estimates rotor position and speed using electrical signals and ANN algorithms. Simulation and experiment results demonstrate accurate position estimation (±1.5°) and efficient torque control. The sensorless direct torque control (DTC)-ANN approach increases the performance, reliability, and cost of stepper motors in robotics, computer numerical control (CNC) machines, and 3D printing.
Intelligent control strategies for grid-connected photovoltaic wind hybrid energy systems using ANFIS Babu, Thiruveedula Madhu; Chenchireddy, Kalagotla; Kumar, Kotha Kalyan; Nehal, Vasukul; Srihitha, Sappidi; Vikas, Marikal Ram
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.
Co-Authors Ajitesh, Dara Ali, Md Yousuf Anirudh, Bakam Arise, Nagasridhar Chenchireddy, Kalagotla Dachepalli, Supriya Dommeti, Tarun Kumar Gollapudi, Srinidhi Kumar, Kotha Kalyan Kummari, Abhishek Mudigondla, Rosaiah Nehal, Vasukul Panjula, Anudeep Rahul, Kanaparthi Rohini, Jakkani Shambukari, Mahith Srihitha, Sappidi Suhas, Mesaragandla Sai Vikas, Marikal Ram