🚗⚡Vehicle Tracking and Performance Monitoring Modules for Electric Vehicle Fleet Management Systems – developed to enhance operational efficiency, optimize energy consumption, and support sustainable transportation goals.

This project implements a Physics-Informed Neural Network (PINN) for electric vehicle range prediction under real traffic conditions. By embedding physical constraints and traffic-aware dynamics into the learning process, the model enhances generalization and robustness compared to purely data-driven models.

Research-grade, AI-augmented Battery Management System (BMS) digital twin for a multi-cell Li-ion pack: ECM, thermal, balancing, SOC estimation (EKF/UKF/LSTM), hybrid fault detection, FMEA/RUL, EV range prediction, plus a Streamlit dashboard. 155 tests passing.