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Leveraging Fuel Cell Technology With AI and ML Integration for Next-Generation Vehicles: Empowering Electric Mobility
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Author(s): R. Muthukumar (Department of Electrical and Electronics Engineering, Erode Sengunthar Engineering College, Erode, India), V. G. G. Pratheep (Department of Mechatronics Engineering, Kongu Engineering College, Perundurai, India), Sultanuddin S. J. (Department of AI&DS, Dhanalakshmi College of Engineering, Chennai, India), Krishnamohan Reddy Kunduru (Department of Engineering Design, Overhead Door Corporation, Lewisville, USA), Praveen Kumar (Department of Electronics and Communication Engineering, Easwari Engineering College, Chennai, India)and Sampath Boopathi (Mechanical Engineering, Muthayammal Engineering College, Namakkal, India)
Copyright: 2024
Pages: 26
Source title:
A Sustainable Future with E-Mobility: Concepts, Challenges, and Implementations
Source Author(s)/Editor(s): Lakshmi D. (VIT Bhopal University, India), Neelu Nagpal (Maharaja Agrasen Institute of Technology, India), Neelam Kassarwani (Maharaja Agrasen Institute of Technology, India), Vishnu Varthanan G. (VIT Bhopal University, India)and Pierluigi Siano (University of Salerno, Italy)
DOI: 10.4018/979-8-3693-5247-2.ch016
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Abstract
The integration of fuel cell technology with artificial intelligence and machine learning in electric vehicles (EVs) has the potential to enhance efficiency, performance, and reliability. Fuel cells, a clean alternative to traditional engines, produce electricity through electrochemical reactions between hydrogen and oxygen, with water vapor as the only byproduct. AI-driven algorithms analyze vast data from sensors and onboard systems, while ML algorithms enable early detection of potential system failures. AI-based driver assist systems can optimize driving behaviors using fuel cell data. However, integrating fuel cell technology with AI and ML faces challenges like data management, algorithm development, and interoperability with existing vehicle systems. Interdisciplinary collaboration between automotive engineers, data scientists, and AI specialists is needed to develop robust, scalable solutions.
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