Smart MPPT Controlled Solar Power with Temperature & Battery Health Sensing

ABSTRACT : The increasing demand for clean and sustainable energy has encouraged the adoption of solar photovoltaic (PV) systems in many power generation applications. However, the efficiency of photovoltaic systems is highly dependent on environmental conditions such as solar irradiance and temperature. To improve the performance of solar energy systems, this work proposes a smart solar charging system that integrates Maximum Power Point Tracking (MPPT) with temperature and battery health monitoring. The proposed system employs the Incremental Conductance MPPT algorithm to ensure that the photovoltaic panel operates at its maximum power point under varying atmospheric conditions. Important electrical parameters including photovoltaic voltage, current, battery voltage, and charging current are continuously monitored using dedicated sensors. Temperature monitoring is also incorporated to enhance battery safety and system reliability. An ESP32 microcontroller is used as the central control unit for implementing MPPT control, sensor data acquisition, and system monitoring. The system also provides real-time visualization through a lightweight web interface and a Python-based monitoring platform. Simulation and hardware results demonstrate that the Incremental Conductance algorithm provides improved tracking accuracy compared with conventional MPPT techniques. The proposed system provides an efficient and economical solution for intelligent solar energy management. KEYWORDS :Solar energy, MPPT, ESP32, Incremental Conductance, Battery monitoring, IoT