PEM Fuel Cells Performance

PEM Fuel Cell Performance: Simulation and Optimization by AI presents novel approaches and methods to improve the performance of PEM fuel cells through multi-objective optimization, computational fluid dynamics, artificial intelligence, and exergy analysis. The book provides solutions to specific problems related to the design and optimization of the PEM fuel cell and its elements, supported by examples, case studies, and numerical simulations. Readers are introduced to the potentials and challenges of PEM fuel cells for various sectors, such as transport, power generation, or hydrogen production. PEM fuel cell performance and optimization is discussed at each stage, covering the design, development, testing, and operation of PEM fuel cell systems and components. For students, the book reviews the basics and applications of PEMFCs and explains the fundamental concepts and theories behind PEMFC performance, supported by exercises and example codes. For researchers the book offers solutions to the challenges in designing and optimizing the PEM fuel cell and its components, and in applying novel approaches and methods to improve performance. This includes examples, case studies, and numerical simulations that illustrate the solutions to specific problems and the applications of novel techniques. Finally, the book provides a guide for engineers and practitioners seeking to enhance the performance, efficiency, durability, and cost-effectiveness of fuel cell systems. This includes practical guidance on elements such as the electrodes, gas diffusion layers, flow fields, two-phase flow, thermal management, and operating conditions. PEM Fuel Cell Performance: Simulation and Optimization by AI offers a valuable guide to students, researchers, engineers, and practitioners working on PEM fuel cells and will be of benefit to interdisciplinary experts working in electrochemistry, materials science, mechanical engineering, chemical engineering, and electrical engineering.

• Explains how to improve PEM fuel cell performance, from the fundamental principles to advanced modelling and optimization techniques
• Introduces simulation approaches, optimization techniques, and data-driven surrogate models based on AI algorithms
• Provides examples, case studies, and numerical simulations that illustrate the solutions to specific problems and the applications of novel techniques
• Explores optimization strategies specifically related to hybrid energy systems, discusses trade-offs, and shares practical examples