IoT Based Condition Monitoring of Solar Powered Electric Vehicle and Predicting Future Power Generation Using AI

The increasing penetration of electric vehicles highlights the energy management and efficiency of maintenance needs, particularly solar-powered EVs. Conventional systems tend not to have predictive analytics and real-time monitoring capabilities, resulting in inefficiencies as well as operating risks. Addressing this gap, the article proposes an IoT-based condition monitoring system for solar-powered EVs. Utilizing the ESP8266 microcontroller and Thing Speak, the system measures and sends key real-time parameters like battery temperature, current, and voltage. The data is visualized and analyzed using cloud-based tools. AI algorithms apply both historical and real-time information to predict solar power generation, allowing proactive maintenance, optimized energy consumption, and early fault detection. Experimental outcomes proved to be more accurate in prediction and anomaly detection early on, resulting in greater reliability and operational efficiency. The system proposed accommodates environmentally friendly transportation and encourages the integration of renewable energy into electric mobility, ensuring sustainability and green innovation.