Estimation of Electric Vehicle Parameters Using Web Portal

Abstract

The transition towards electric vehicles (EVs) necessitates accurate estimation of various parameters crucial for understanding EV performance and optimizing user experience. This abstract presents the design and implementation of a web portal aimed at estimating key parameters of electric vehicles. The portal serves as a user-friendly platform for individuals and organizations to gain insights into EV characteristics without the need for specialized software or expertise. The portal facilitates the estimation of essential EV parameters such as battery capacity, range, charging time, and efficiency. Leveraging mathematical models, empirical data, and possibly machine learning algorithms, the portal offers users the ability to input relevant variables such as vehicle specifications, driving conditions, and charging infrastructure details. The backend of the portal is developed to handle complex calculations and data processing, ensuring accurate estimation results. Integration with databases may enable the storage of user inputs, historical data, and model updates for continuous improvement. On the frontend, the web portal features an intuitive and interactive user interface designed with HTML, CSS, and JavaScript. The interface guides users through the input process and presents estimation results in a clear and comprehensible manner. Visualization tools may be incorporated to enhance user understanding of the estimated parameters.