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Metaheuristic algorithms for parameter estimation of DC servo motors with quantized sensor measurements Mishra, Debani Prasad; Behera, Sandip Ranjan; Dash, Arul Kumar; Ojha, Prajna Jeet; Salkuti, Surender Reddy
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i1.pp101-108

Abstract

Manufacturing, aviation, and robotics have increased servo motor use due to their precision, reliability, and adaptability in various applications. This study compares three metaheuristic techniques for servo motor model parameter estimation with sensor measurement quantization, focusing on their accuracy and efficiency. Armature resistance, back electromotive force (EMF) constant, torque constant, coil inductance, friction coefficient, and rotor-load inertia are crucial to servo motor behavior prediction, significantly impacting overall system performance. Each approach was rigorously tested and analyzed to evaluate its effectiveness in predicting servo motor characteristics. The results revealed that particle swarm optimization and the firefly algorithm delivered comparable performance, particularly excelling in scenarios where sensor measurement quantization introduced noise or imprecision in the data. These methods demonstrated strong resilience and accuracy under such challenging conditions. In contrast, the genetic algorithm did not perform as well, falling short when compared to the other two techniques in handling noisy or imprecise data, indicating its relative inefficiency in such environments. These findings give servo motor designers and engineers across industries a powerful tool for performance prediction.
Cyber-physical resilience system for anomaly detection in industrial environments Mishra, Debani Prasad; Lenka, Rakesh Kumar; Yagyna Duthsharma, Rampa Sri Sai; Kumar, Pavan; Bhardwaj, Lakshay; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp497-505

Abstract

This work explores the topic of cybersecurity in the context of electric vehicles (EVs). It ensures the resilience of cyber-physical systems against anomalies, which is paramount for maintaining operational efficiency and safety. This paper presents a cyber-physical resilience system (CPRS) customized for anomaly detection. Maintaining operational efficiency and safety in today’s networked industrial contexts requires that cyber-physical systems be resilient to abnormalities. With an emphasis on EVs, this research introduces a unique CPRS designed for anomaly detection in industrial settings. By utilizing the combination of digital and physical elements, the CPRS uses sophisticated monitoring and reaction systems to identify and address irregularities instantly. The process includes creating algorithms for anomaly detection and putting in place a framework that is responsive enough to change with the dangers that it faces. The efficiency of the CPRS in detecting unusual behaviors in EVs is demonstrated by experimental findings, which also improve the overall resilience of the system. Moreover, the research’s ramifications go beyond EVs to include a variety of industrial settings, providing valuable information for the development and execution of resilient cyber-physical systems. This paper highlights the significance of proactive resilience measures in protecting critical infrastructure and advances anomaly detection approaches.
Load forecasting of electrical parameters: an effective approach towards optimization of electric load Mishra, Debani Prasad; Pradhan, Rudranarayan; Priyadarshini, Ananya; Das, Subha Ranjan; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp708-716

Abstract

The increasing need for energy and the increasing cost of electricity have prompted the development of smart energy optimization systems that can help consumers reduce their electricity consumption and minimize costs. These systems are developed on the concept of a “smart grid” which is a digitalized and intelligent energy network that provides help in the efficient distribution of energy. Load forecasting plays a crucial role in the precise prediction of uncontrollable electrical load. Long-term load analysis predicts a load of more than one year and helps in the planning of power systems whereas short-term and medium-term load forecasting helps in the supply and distribution of load, maintenance of load system, ensuring safety, continuous electricity generation, and cost management. Machine learning (ML) focuses on the development of smart energy optimization systems by enabling intuitive decision-making and reciprocation to sudden variations in consumer energy demands. This study focuses on the consumption of consumer electricity and provides a solution regarding the optimized methods that will predict future consumption based on previous data and help in reducing costs and preserving renewable energy. This research promotes sustainable energy usage. The use of ML models enables intelligent decision-making and accurate predictions, making the system an effective tool for managing electricity consumption.
Enhancing logo security: VGG19, autoencoder, and sequential fusion for fake logo detection Mishra, Debani Prasad; Ojha, Prajna Jeet; Dash, Arul Kumar; Sethy, Sai Kanha; Behera, Sandip Ranjan; Salkuti, Surender Reddy
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp506-515

Abstract

This paper deals with a way of detecting fake logos through the integration of visual geometry group-19 (VGG19), an autoencoder, and a sequential model. The approach consists of applying the method to a variety of datasets that have gone through resizing and augmentation, using VGG19 for extracting features effectively and autoencoder for abstracting them in a subtle manner. The combination of these elements in a sequential model account for the improved performance levels as far as accuracy, precision, recall, and F1-score are concerned when compared to existing approaches. This article assesses the strengths and limitations of the method and its adapted comprehension of brand identity symbols. Comparative analysis of these competing approaches reveals the benefits resulting from such fusion. To sum up, this paper is not only a major contribution to the domain of counterfeit logo detection but also suggests prospects for enhancing brand security in the digital world.
Optimizing vehicle-to-grid scheduling and strategic placement for dynamic wireless charging of electric vehicles Mishra, Debani Prasad; Sahay, Sanchita; Kumar, Ayush; Salkuti, Surender Reddy
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.pp328-337

Abstract

Dynamic wireless charging of electric vehicles (EVs) has become popular in intelligent transportation systems (ITS). However, both economic and smart city perspectives should be taken into account in the integration of wireless charging infrastructure for electric vehicles. Current research mainly focuses on power transfer (PT) or autonomous vehicle-to-grid (V2G) transfer. This paper presents a multilayered approach that combines optimal PT planning based on urban traffic and energy efficiency data with dynamic V2G planning. Simulation results show that the efficiency of PT placement and V2G scheduling increases and provides good results for smart city enterprises. This multilayered approach not only optimizes the efficiency of power transfer placement and V2G scheduling but also positions itself as a pivotal driver for the sustainable evolution of urban mobility. As dynamic wireless charging continues to shape the future of intelligent transportation systems, this research stands at the intersection of technological innovation, economic prudence, and urban planning, offering a blueprint for the seamless integration of EVs into the fabric of smart cities.
Comparison of MPP methods for photovoltaic system Mishra, Debani Prasad; Senapati, Rudranarayan; Biswal, Prabin; Satapathy, Swayamjyoti; Sahu, Smruti Susmita; Salkuti, Surender Reddy
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.pp338-346

Abstract

Solar electricity is usually a ubiquitous photovoltaic (PV) power source that converts sunlight into electricity. This makes solar energy a key factor in meeting the growing global demand. However, solar energy production from photovoltaic cells can be limited by many factors, so the power source needs to be optimized to reach the maximum level. One of the crucial technologies to enhance the power production of photovoltaic structures is maximum power point tracking (MPPT) measurement. This technology increases energy production by providing many advantages such as security, freedom, maximum energy efficiency, and environmental protection. MPPT continuously monitors the maximum power point of the photovoltaic structure to ensure the system operates at peak efficiency. This technology is indispensable in today’s solar systems, enabling the use of solar energy and reducing dependence on fossil fuels. By optimizing solar energy production, MPPT technology plays a crucial role in supporting the future of energy. It helps reduce climate change and promotes environmentally friendly practices through the use of renewable energy. MPPT technology also increases solar reliability, reduces maintenance costs, and improves overall performance. This makes MPPT an essential part of the modern solar system, ensuring they are efficient and effective.
Empowering microgrids: harnessing electric vehicle potential through vehicle-to-grid integration Mishra, Debani Prasad; Senapati, Rudranarayan; Samal, Sarita; Rai, Niti Rani; Behera, Niharika; Salkuti, Surender Reddy
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1422-1430

Abstract

Electric vehicles (EVs) can potentially be integrated into microgrids via vehicle-to-grid (V2G) technology, which enhances the energy system's stability and durability. This paper provides an in-depth examination and evaluation of V2G integration in microgrid systems. It analyses the present state of research as well as possible uses, challenges, and directions for V2G technology in the future. This paper addresses the technological, economic, and regulatory aspects of implementing V2G and provides case studies and pilot projects to shed light on potential benefits and barriers associated with its adoption. The research highlights how V2G contributes to more efficient integration of renewable energy sources, grid stabilization, and cost savings for EV owners. It also addresses the latest developments in technology and proposed laws aimed at encouraging growing applications of V2G.
Predictive modeling of electric vehicle loads through driving behavior analysis Mishra, Debani Prasad; Pradhan, Rudranarayan; Singh, Saksham; Singh, Anurag; Kumar, Ayush; Salkuti, Surender Reddy
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1431-1439

Abstract

Electric vehicles (EVs) can potentially be integrated into microgrids via vehicle-to-grid (V2G) technology, which enhances the energy system's stability and durability. This paper provides an in-depth examination and evaluation of V2G integration in microgrid systems. It analyses the present state of research as well as possible uses, challenges, and directions for V2G technology in the future. This article addresses the technological, economic, and regulatory aspects of implementing V2G and provides case studies and pilot projects to shed light on potential benefits and barriers associated with its adoption. The research highlights how V2G contributes to more efficient integration of renewable energy sources, grid stabilization, and cost savings for EV owners. It also addresses the latest developments in technology and proposed laws aimed at encouraging growing applications of V2G.
Study of the development of tandem solar cells to achieve higher efficiencies Mishra, Debani Prasad; Sahu, Jayanta Kumar; Subudhi, Umamani; Sahoo, Arun Kumar; Salkuti, Surender Reddy
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.pp647-655

Abstract

Tandem solar cells are the brand-new age revolution within the photovoltaic (PV) enterprise thanks to their higher power conversion efficiency (PCE) capability as compared to single-junction solar cells, which are presently dominating, however intrinsically restrained. With the appearance of steel halide perovskite absorber substances, manufacturing extremely efficient tandem solar cells at an inexpensive price can profoundly regulate the future PV landscape. It has been formerly seen that tandem solar cells primarily based on perovskite have confirmed that they can convert mild more efficiently than stand-alone sub-cells. To reap PCEs of greater than 30%, numerous hurdles have to be addressed, and our understanding of this interesting era has to be accelerated. On this, a technique of aggregate of substances was followed and via a modified numerical technique, it was decided what preference of substances for the pinnacle and bottom sub-cell consequences in a better fee of electricity conversion efficiency (PCE). Through this study, it was discovered that the use of germanium telluride (GeTe) backside subcellular together with perovskite (MAPbI3-xClx) as pinnacle subcell can offer an excessive performance of 46.64% compared to a tandem mobile with perovskite (MAPbI3)/CIGS and perovskite (MAPbI3)/GeTe which produce decrease efficiencies. SCAPS-1D was used to evaluate and simulate the overall performance of the developed tandem cells.
Advancements in electric vehicle safety and charging infrastructure Mishra, Debani Prasad; Senapati, Rudranarayan; Kedia, Nisha; Sahay, Sanchita; Swain, Raj Alpha; Salkuti, Surender Reddy
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.pp1332-1339

Abstract

In electric vehicles (EVs), safety measures must be taken to prevent dangerous accidents. Safety regulations must be in place for two important things: electric or EV batteries and EV equipment. Operating an electric vehicle charging stations (EVCS) is a challenging task. This holistic approach is used to evaluate when renewable energy is produced. It's best to focus on the popularity of EVs as more and more people choose this mode of transportation. It is important to know that power plants can be risky. Therefore, safety issues related to EV charging must be addressed quickly and appropriately. Potential safety issues with EVs include overcurrent, ground faults, and overheating. If the charging system does not work, the electric car's battery may heat up and catch fire, and overcharging may cause other problems. To avoid security risks, you must comply with security regulations, use payment devices that meet security requirements, and follow the manufacturer's instructions.