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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE) International Journal of Advances in Applied Sciences
Ambati, Giriprasad
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Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Li-Fi technology for automated transport Kumari, Popuri Rajani; Suneetha, Chalasani; Anil Kumar, Maddali; Mrudula, Tangirala; Venkatachalam, Anbumani; Venkata Rajanna, Bodapati; Ambati, Giriprasad
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1129-1136

Abstract

India is now one of the countries that is growing quickly worldwide. Today, practically for everything, a vehicle is necessary. Vehicle production is growing rapidly. One of the downsides of this enormous increase is the ineffective management of traffic. The well-planned expansion of transport organizations has resulted in a variety of challenges with travel. It is detrimental to both mankind and the economy when emergency vehicles like ambulances and fire engines are late in arriving. Smart transport is the most effective strategy to lower vehicle accidents and communicate with other cars to open a way for emergency vehicles. Here, the preliminary ideas and findings of a small-scale model of an automated transport system are presented using an innovative discovery known as Li-Fi, also known as light-fidelity. Full duplex communication is accomplished with Li-Fi, in which light is modified at speeds that are too rapid for the eye to follow. Li Fi may be used to create intelligent transportation systems since it offers various advantages over other communication protocols.
Analysis of different converter topologies for EV applications Rajanna, Bodapati Venkata; Krishnaiah, Kondragunta Rama; Girija, Sakimalla Prabhakar; Ahammad, Shaik Hasane; Najumunnisa, Mohammad; Inthiyaz, Syed; Eragamreddy, Gouthami; Ambati, Giriprasad; Kolukula, Nitalaksheswara Rao
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i1.pp518-532

Abstract

Electric vehicles (EVs) are gaining global prominence due to their high efficiency, low noise, and minimal carbon emissions. A critical aspect of EV performance lies in the interaction between energy storage systems (ESS) and power converters. Nonetheless, power delivery from storage units tends to be unreliable and needs strong converter units for effective and stable energy transmission. Several forms of direct current-to-direct current conversion systems used in electric vehicles are thoroughly examined in the paper, including both isolated and non-isolated designs such as those with the cuk, flyback, and push-pull architectures. The paper looks at converter categorization, control methods such as proportional-integral and artificial neural networks, as well as the method of modulation using unipolar and bipolar sinusoidal pulse-width modulation (PWM). Additionally, the role of optimization algorithms in improving converter performance is explored. Simulations were conducted using MATLAB/Simulink to evaluate each topology under varying load and input voltage conditions. The results demonstrate that the Push-Pull converter has the best efficiency for high-power applications, while the Cuk and Flyback converters are best for applications requiring continuous current and low-power, compact designs, respectively. This research offers insights for choosing optimal converter structures to improve energy efficiency and reliability of systems in electric vehicles.
Machine learning-driven prognostics for lithium-ion batteries: enhancing RUL prediction and performance in smart energy storage systems Rajanna, Bodapati Venkata; Seenu, Aaluri; Krishnaiah, Kondragunta Rama; Peddinti, Anantha Sravanthi; Prakash, Nelaturi Nanda; Seshukumari, Bandreddi Venkata; Ambati, Giriprasad; Ahammad, Shaik Hasane; Kumar, Chakrapani Srivardhan; Rao, Allamraju Shubhangi
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp257-274

Abstract

In the evolving landscape of energy systems, batteries play a critical role in enabling hybrid and stand-alone renewable energy storage solutions. Precisely estimating battery life and remaining useful operational life will go a long way in enhancing the efficiency of the system with assured reliability in smart power storage devices. This report comprehensively surveys advanced approaches in the management of batteries through state-of-the-art artificial intelligence tools-support vector machines, relevance vector machines (RVM), long short-term memory (LSTM) models, and bayesian filters-that are being used with a view to enhancing remaining useful life (RUL) estimates and making real-time system health monitoring capabilities possible. Modeling approaches surveyed include state estimation, capacity, and thermal management, while discussing their applicability to lithium-ion batteries. The review also explores publicly available battery datasets, feature engineering strategies, and hybrid diagnostic frameworks. A technoeconomic perspective is provided to assess system performance in renewable-integrated power grids. This paper aims to consolidate current knowledge, provide comparative insights into the strengths and limitations of different approaches, and highlight open research challenges to guide future developments in smart AI-enabled battery systems that support sustainable and resilient energy infrastructure.
Co-Authors Ahammad, Shaik Hasane Anil Kumar, Maddali Eragamreddy, Gouthami Girija, Sakimalla Prabhakar Inthiyaz, Syed Kolukula, Nitalaksheswara Rao Krishnaiah, Kondragunta Rama Kumar, Chakrapani Srivardhan Kumari, Popuri Rajani Mrudula, Tangirala Najumunnisa, Mohammad Peddinti, Anantha Sravanthi Prakash, Nelaturi Nanda Rajanna, Bodapati Venkata Rao, Allamraju Shubhangi Seenu, Aaluri Seshukumari, Bandreddi Venkata Suneetha, Chalasani Venkata Rajanna, Bodapati Venkatachalam, Anbumani