n this research paper, we have discussed different types of steering geometry such as Ackerman, anti-ackerman and Davis steering geometry. We have also discussed the advantages and disadvantages of all three types of geometry and implemented the best steering geometry for our four-wheel effic-ycle. We have done three iterations to determine the best Ackerman percentage, critical velocity and steering ratio.
This paper investigates the role of supercapacitor technology in enhancing traction efficiency and reducing infrastructure costs in metro rail systems by replacing conventional track-based electrification. Traditional metro systems rely heavily on continuous electrification through overhead lines or third-rail systems, leading to high capital expenditure, complex infrastructure requirements, and significant energy losses, especially in urban environments with frequent stops. Whereas, the quick charging, adequate regenerative braking, and longevity of supercapictor powered trains enables them preferred choice for local railroad lines.
This paper presents a single Quadratic Unconstrained Binary Optimization (QUBO) model of the combined optimization of both active and reactive power dispatch of an Electric Vehicle Aggregator (EVA). Its methodology integrates a new tri-layered, nested optimization framework that streamlines the process of selecting an optimum timetable of the EVA, checking its feasibility with grid limits at the Distribution System Operator (DSO) tier, and then distributing the ultimate schedule to each EV. The resulting framework results in a multi-level, comprehensive evaluation of the system, which generates economically optimal results of both the EVA and the DSO.
Without air, humanity could not possibly survive. Air quality is negatively affected by continuous changes in almost every area of modern human civilization, posing a threat to sustainable development. By integrating sustainable practices into air quality monitoring and forecasting, we can aim to minimize the generation of risky contaminants and reduce the total environmental footprint of transportation, business, and home approaches.
Lately, navigating and selecting items in shopping centers has become a daily activity in urban areas, with a multitude of individuals engaging in shopping, particularly during holidays and weekends. The peak shopping periods coincide with special offers and discounts, leading people to purchase a variety of items and place them in shopping carts. Upon completing their purchases, customers are required to visit the billing counter for payment and invoicing. At the charging counter, the clerk readies the receipt utilizing a standardized tag scanner, a tedious cycle that frequently brings about lengthy lines. To overcome this problem, this paper proposed a smart shopping cart using RFID technology.
This work presents the design and development of an autonomous holonomic drive robot system with object detection capability, enabling movement in all directions using computer vision and Mecanum wheels. Computer visionbased object detection allows the robot to recognize its surroundings, categorize objects, and respond promptly, while the drive system facilitates smooth movement of the robot across its entire workspace. The capabilities of the robot are further enhanced using OpenCV and YOLO technology to enable effective movement and interaction in changing environments.
Modern Drones are rapidly transforming into intelligent, interactive and smart aerial systems that are capable of communicating in real-time and make autonomous decisions. This paper investigates the mechanism behind voice command recognition, two-way communication, and virtual assistant integration to boost UAV capabilities. The application of Hidden Markov Models (HMM) and Maximum Likelihood Linear Regression (MLLR) techniques in the field of speech recognition allows drones to understand and process voice instructions.
Solar power has come a long way with the recent developments in photovoltaic (PV) technology. The emerging PV technologies which will be commercially available like perovskite and organic solar cells, are discussed along with their pros and cons. This article reviews the recent improvements in PV accessibility, affordability, and efficiency. New materials and techniques are being researched for better and economical solar cells. A comprehensive review of thin film solar cell (TFSC) technology is presented in this study, including its manufacturing processes, classification, principles, advantages, disadvantages, challenges, and future prospects.
Accurate wind power forecasting at the turbine level is pivotal for optimizing grid integration, strengthening energy management strategies, and maximizing operational efficiency in the large-scale wind farms. Complex spatial interconnections between turbines and dynamic wake interactions influence power generation and substantially not included in conventional forecasting approaches. We propose a Wake-Aware SpatioTemporal Graph Neural Network (WAST-GNN) framework for turbine-level wind power prediction. In the proposed model, wind turbines are modelled as nodes of a graph and the wakes and spatial proximity as connectedness of the graph.
