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Advancements in Electric Vehicle Management System: Integrating Machine Learning and Artificial Intelligence
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Author(s): D. Godwin Immanuel (Department of Electrical and Electronics Engineering, Sathyabama Institute of Science and Technology, India), Gautam Solaimalai (U.S. Bank, USA), B. M. Chandrakala (Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Bengaluru, India), V. G. Bharath (Vessels Engineers, Bangalore, India), Mukul Kumar Singh (Department of Electrical Engineering, MJP Rohilkhand University, Bareilly, India)and Sampath Boopathi (Department of Mechanical Engineering, Muthayammal Engineering College, Namakkal, India)
Copyright: 2024
Pages: 21
Source title:
Semantic Web Technologies and Applications in Artificial Intelligence of Things
Source Author(s)/Editor(s): Fernando Ortiz-Rodriguez (Tamaulipas Autonomous University, Mexico), Amed Leyva-Mederos (Universidad Central "Marta Abreu" de Las Villas, Cuba), Sanju Tiwari (Tamaulipas Autonomous University, Mexico), Ania R. Hernandez-Quintana (Universidad de La Habana, Cuba)and Jose L. Martinez-Rodriguez (Autonomous University of Tamaulipas, Mexico)
DOI: 10.4018/979-8-3693-1487-6.ch018
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Abstract
The chapter discusses the advancement of electric vehicle (EV) management systems, emphasizing the role of machine learning and artificial intelligence in optimizing vehicle dynamics, battery management, charging infrastructure, and user preferences. These technologies can enhance performance, efficiency, and user experience by adapting to dynamic driving conditions, optimizing energy consumption, and providing personalized experiences. The chapter also addresses challenges like data privacy, computational complexity, and interoperability, suggesting solutions and highlighting the need for collaborative research initiatives and regulatory frameworks for responsible ML and AI deployment in the EV industry.
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