Energy Prediction for Automobile Air Conditioning Systems

Significant energy wastage and increased CO2 emissions from automobile air conditioning systems highlight the critical need for enhanced energy prediction and management. This study investigates the potential of machine learning algorithms for energy prediction in A/C systems, focusing on the Toyota Prius Hybrid model. By integrating vehicle data with external weather information, we developed a predictive model that accurately forecasts energy usage and identifies key factors influencing efficiency. These findings could facilitate the creation of intelligent control systems for automotive air conditioning, leading to enhanced energy savings and reduced emissions.