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Analyzing Fuel Cell Vehicles Through Intelligent Battery Management Systems (BMS): AI and ML Technologies for E-Mobility
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Author(s): Putchakayala Yanna Reddy (Department of Electrical & Electronics Engineering Department, Bharath Institute of Engineering and Technology, India), Balpreet Singh Madan (Department of Art and Design, School of Design, Architecture, and Planning, Sharda University, Greater Noida, India), Harishchander Anandaram (Department of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Coimbatore, India), Praveen Rathod (Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, Pune, India), S. Vasanthaseelan (Department of Mechanical Engineering, Sri Krishna College of Technology, Coimbatore, India)and S. Boopathi (Muthayammal Engineering College, 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.ch016
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Abstract
Integrating artificial intelligence (AI), internet of things (IoT), and machine learning (ML) technologies into fuel cell systems offers numerous benefits, applications, and opportunities for advancement across various sectors. This chapter explores the synergistic potential of AI, IoT, and ML in fuel cell integration, outlining their advantages, applications, challenges, and potential solutions. By leveraging AI for predictive maintenance, optimizing operating conditions through IoT sensors, and employing ML algorithms for efficiency enhancements, fuel cell systems can achieve higher performance and reliability. Real-world case studies and examples demonstrate successful integration in sectors such as transportation, energy production, and manufacturing. Moreover, this chapter discusses future prospects, including advancements in data analytics, system optimization, and scalability, driving innovation in fuel cell technology integration with AI, IoT, and ML.
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