Rasa-Powered Conversational AI Framework for Intelligent Electric Vehicle Trip Planning and Energy Management

T, Phanendra (Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, India)
G, Swapna (Koneru Lakshmaiah Education Foundation, India)
M, Vishnuvardhan (Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, India)
Rao, K V Govardhan
Rakesh, T
Kumar, M Kiran

Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol 13, No 4: December 2025

The rapid growth of Electric Vehicles (EVs) calls for intelligent solutions to optimize grid stability and enhance user experience. This paper proposes a geo-optimized, user-centric EV management system integrating open-source geospatial tools with Rasa-based Natural Language Understanding (NLU). Through an interactive conversational interface, EV owners receive real-time trip planning recommendations based on parameters such as State of Charge (SoC), charging point availability, and route efficiency. The system utilizes APIs for real-time geolocation, charging station data, and Battery Management System (BMS) insights to determine optimal charging locations, durations, and trip costs. Extensive testing demonstrates improved energy management and route planning efficiency, highlighting the system’s potential for smart and sustainable EV infrastructure development.