Intelligent Battery Management System using Machine Learning with Dual axis Solar Tracking System

Electric vehicles becoming more and more popular around the world as a result of the rising demand for environmentally friendly transportation. Integrating solar power into charging systems presents a viable way to support the EV charging infrastructure and lessen dependency on grid electricity. The system majorly consists of solar panels, a control unit based on raspberry pi, light sensors, a motor controller, and the battery management system. The input received by control unit in terms of illumination and directionality is provided to it by light sensors. These details are analysed to calculate an ideal position where the solar panel must be moved as determined by the control unit through the control of the motor controller The dual-axis solar tracking technology continuously aligns the solar panels with the sun's position to maximize energy collecting. The panels' horizontal and vertical axes can be dynamically adjusted to optimize amount of solar energy captured throughout the day. The BMS effectively keeps an eye on and regulates important factors like BMS guarantees optimal state-of-charge and overall battery health, improving safety and longevity.