• Rudraksh Kore
• Anjalee Kamble
• Mr. Saugat Das

This paper presents an intelligent Electric Vehicle (EV) rental platform designed to enhance user experience and promote sustainable transportation. The proposed system integrates machine learning-based trip prediction, real-time charging station locator, and dynamic pricing mechanisms. It aims to address major challenges such as range anxiety, uncertain charging availability, and inefficient trip planning faced by EV users. By analyzing historical trip data, the system accurately predicts energy consumption and required charging stops. Real-time mapping services help users locate nearby charging stations along their route. Dynamic pricing ensures transparent and fair cost estimation based on distance and travel time. The platform also provides real-time vehicle availability to streamline the booking process. The integrated approach enables better trip planning and improved operational efficiency. Experimental results demonstrate enhanced prediction accuracy and reduced travel uncertainty. Overall, the system supports wider EV adoption by delivering a smart, reliable, and user-friendly rental experience.

E.V, Rental Car Application, Dashboard, Google Maps, Secure Payments.

"EV Car Rental System with Charging Station Locator and Trip Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 2, page no.c555-c558, February-2026, Available :http://www.jetir.org/papers/JETIR2602281.pdf

"EV Car Rental System with Charging Station Locator and Trip Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 2, page no. ppc555-c558, February-2026, Available at : http://www.jetir.org/papers/JETIR2602281.pdf