<![CDATA[Electric vehicles (EVs) are at the forefront of global initiatives to reduce greenhouse gas emissions and tackle urgent environmental challenges. This study presents a comprehensive review of fast charging technologies and DC-DC converters, which are crucial in the development of EV infrastructure. It explores various DC-DC converter topologies used in EVs and examines the challenges associated with fast charging infrastructure. Additionally, the study analyzes the application of artificial neural networks (ANNs) for predicting junction temperatures of electronic components in EVs. The findings indicate that ANNs enhance the accuracy of temperature predictions, contributing to performance optimization and extended component lifespan. Furthermore, the study underscores the significance of energy management technologies, particularly the integration of hybrid energy storage systems (HESS) that combine batteries and supercapacitors. The study’s implications include recommendations for advancing fast charging technology, improving thermal management, and educating drivers to enhance EV energy efficiency. Despite existing challenges, technological advancements in these areas hold great promise for accelerating EV adoption and supporting global decarbonization efforts.Keywords: Electric Vehicle (EV), Artificial Neural Network (ANN) Model, Thermal Management, Hybrid Energy Storage System (HESS), Energy Management.]]>
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