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Leveraging Fuel Cell Technology With AI and ML Integration for Next-Generation Vehicles

R. Muthukumar, V. G. Pratheep, S. J. Sultanuddin, Krishnamohan Reddy Kunduru, Praveen Kumar R, Sampath Boopathi

2024Advances in mechatronics and mechanical engineering (AMME) book series22 citationsDOI

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.

Topics & Concepts

ScalabilityAutomotive industryFuel cellsInteroperabilityComputer scienceReliability (semiconductor)ElectricitySystems engineeringAutomotive engineeringEngineeringDatabaseElectrical engineeringAerospace engineeringWorld Wide WebPhysicsQuantum mechanicsChemical engineeringPower (physics)Fuel Cells and Related MaterialsVehicle emissions and performanceElectric and Hybrid Vehicle Technologies
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