Business Viability and Sustainability of a Prototype Solar-Powered Electric Vehicle: A Machine Learning Approach
Résumé
The transition to renewable energy is essential for long-term sustainability, particularly as fossil fuel reserves decline.This study investigates the development and economic feasibility of an affordable solar-powered vehicle tailored for emerging markets.The vehicle aims to reduce dependence on fossil fuels, mitigate air pollution, and offer financial advantages over traditional internal combustion engine (ICE) vehicles.The solar-powered vehicle operates by harnessing solar energy to charge a deep-cycle battery that powers an electric motor, eliminating fuel costs and emissions.Key engineering efforts focused on optimizing chassis design for stability and durability across varied driving conditions.To evaluate performance and predict user benefits, machine learning techniques were employed.A linear regression model assessed charging efficiency under different conditions, while a Random Forest Regression model was used to analyze market demand and travel patterns.Predictive models accurately forecasted travel range and energy consumption, enabling better planning and efficiency.The Solar-powered vehicle demonstrates strong potential for cost savings, low maintenance, and environmental impact reduction.Its integration of solar energy and AI analytics makes it a scalable, data-driven solution for sustainable mobility in emerging markets.
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