Cognitive radio (CR) technology enables a secondary user (SU) to make the most use of the licensed spectrum when the primary user (PU) is inactive, hence increasing spectrum efficiency. SUs are required to complete the spectrum sensing process to identify the spectrum utilization. It is required to effectively detect PU signal to SU for using the idle licensed spectrum bands. Even though various spectrum sensing techniques are designed in CR networks, designing test statistics still results in a complex task. To solve spectrum scarcity issues and to increase spectrum utilization, Honey Badger Remora Optimization-based AlexNet (HBRO-based AlexNet) is developed in this research and the test statistics model is modeled with a deep learning approach with signal parameters, like signal energy, and Eigen statistics. However, SU can use AlexNet to boost the spectrum efficiency of PU's licensed spectrum, which will then permit an increase in the chance of detection in the CR network (CRN). Though considering signal-to-noise ratio (SNR) at 5 dB, the proposed spectrum sensing approach yields the probability of detection and probability of false alarm for the Rician channel as 1 and 0.999, respectively.

The objective of this work is to demonstrate a design-centric dynamic teaching technique in a power electronics course for undergraduate students at the National Institute of Technology Raipur. This strategy intends to provide a systematic approach for designing a converter over the course of a semester in order to acquire higher-order cognitive skills. Traditional teaching approaches, as well as several recently proposed techniques in the literature, are inadequate at fostering higher-order cognitive skills. Considering the aforementioned challenges, the proposed methodology involves dividing the enrolled students into groups exhibiting students of varying academic proficiency levels. These groups will be tasked with the completion of a semester-long project that entails the design and development of a DC-DC boost converter, from conception to a fully functional prototype. As a result, this technique will gradually instill many desirable skill sets such as managerial, communication, problem solving, critical thinking, software, and hardware development competency, and therefore they will be able to establish a creative mentality. Furthermore, these skill sets will drive students to pursue higher education, technical jobs, and research possibilities in the future. The course saw an increase in student interest and proficiency in practice.

Electric vehicles are popular in these days and gaining height in all country of the world because of the pollution due to fossil fuel and green house effect. The battery powered electric vehicle is going to popular in the crowd but also this segment is suffering from few problems like range anxiety, efficiency, fixed battery size, charging time, etc. The objective is to develop an efficient and reliable solution that allows EV owners to replace their depleted batteries quickly and easily with fully charged ones, eliminating the need for lengthy charging times. The investigation involves a thorough analysis of existing swappable battery technologies, considering factors such as battery design, compatibility, safety, and operational considerations. The proposed solution presents a novel battery design that incorporates standardized connectors and protocols to ensure seamless integration and compatibility across different EV models. The methodology outlines the development process, including battery pack design, mechanical considerations, and electrical system integration. This research contributes to the advancement of sustainable transportation by providing an innovative solution to enhance the practicality and accessibility of electric vehicles through efficient swappable battery technology.

Electric Vehicle (EV) is getting popular day by day and most of the countries in the world are converting their transport system to electric infrastructure. Battery pack is one of the main sources of energy for EV. Fixed batteries of different power are utilized in different types of EVs. The objective of this research is to explore the potential of reconfigurable battery systems in addressing the limitations of fixed battery sources in electric vehicles (EVs). The investigation involves a comprehensive analysis of the current challenges associated with fixed battery sources, including limited range, long charging times, battery degradation, inflexibility. The research focuses on developing a reconfigurable battery solution that allows for flexible battery configurations, enabling enhanced range, reduced charging times, improved battery performance, interchangeability between different EV models. The methodology encompasses battery design and engineering, integration with EV systems, testing and evaluation of reconfiguration mechanisms, and performance analysis through simulations and experimental validation. The results of this research provide insights into the feasibility, benefits, and contributing to the advancement of sustainable transportation and electric vehicle technology.

In this study, a comprehensive analysis of existing charging stations and their emerging technologies is conducted to optimize the usage and intelligence of the existing charging station. Charging stations are currently designed for specific vehicles, such as two-wheelers, four-wheelers, and heavy commercial vehicles. The research proposes a solution that designs and analyzes smart charging stations, which can transform any existing charging station into a smart one. The technique describes the operation of smart charging stations, which employ a switching mode that accommodates various segments of electric vehicles. The analysis of switching mode involves consideration of power, current, and voltage, duty cycle is adjusted to achieve desired voltage level. Furthermore, the methodology demonstrates that the smart charger can communicate with electric vehicles battery packs and adapt the desired output power based on the battery pack configuration.

In this paper, an improved non-isolated multiple input boost dc-dc converter (MIBC) with an energy storage unit has been proposed. The topology can transfer energy from numerous energy sources to the load simultaneously or independently. The circuit architecture so designed that it has less total peak inverse voltage (TPIV) and less total current stress than a conventional converter. The topology is provided with an energy storage unit (battery), which realizes the bidirectional power flow operation for simultaneous absorption of excess energy generated by the input sources. The advantages of the proposed topology include the simple structure and reduced number of components (active/passive switches, inductors, capacitors, and current/voltage sensors). The proposed converter is investigated with different operational modes and design considerations. For gate pulse generation flip-flops are used which have the capability to operate for a wide range of duty ratios. For validation, the topology has been modeled and simulated in MATLAB/Simulink environment. The suitability of the proposed topology for photovoltaic applications has been validated with the obtained results.

Field oriented control (FOC), also known as vector control of induction motor drives is very useful technique to obtain high performance speed response. Implementation of field oriented control requires the knowledge of instantaneous magnitude and position of rotor flux and load behavior for the correct dimensioning of an induction motor. This paper demonstrates estimation of feedback signals in a three phase induction motor drive. The instantaneous magnitude and position of rotor flux and load torque estimator, in the form of a two stage neural network is presented. The neural network is able to accurately estimate these parameters of an induction motor. The observations indicate that the neural network estimation may be a feasible alternative to other rotor flux and load torque estimation methods like a programmable DSP kit. The comparative performance of both has been presented in this work with the help of a practical three-phase induction motor drive.