Optimizing the Performance of Solar-Powered Electric Vehicles through Integrated Solar Panel Systems

Abstract

Solar-powered electric vehicles have become a viable way to decrease carbon emissions and improve energy efficiency in the current era of concern for the environment and the push for sustainable mobility. By skilfully incorporating cutting-edge solar panel systems into their design, this initiative seeks to transform the performance of solar-powered electric vehicles. The main objective is to effectively use solar energy to increase the overall efficiency of electric vehicles, which will increase their range and lessen their dependency on traditional grid electricity. In order to do this, the study uses Artificial Neural Networks (ANNs) to precisely forecast solar power generation and load demand. By aligning energy demand with the supply of renewable solar energy, these forecasts play a critical role in power supply system optimization. In order to achieve the best possible balance between energy demand and the use of renewable energy sources, the project also investigates an innovative Hybrid Artificial Bee Colony-Gravitational Optimization Algorithm (ABC-GOA). In accordance with the current global trend towards greener mobility options, this study represents a critical step towards sustainable and sustainable transportation solutions.