Fuel Cell Technologies

White paper on achieving high Fuel cell system performance and lower defects through AI and ML

Maximizing Fuel Cell Electrochemical Performance

For maximizing electrochemical performance of the fuel cell stacks across various applications including stationary, transportation, portable, and reducing the cost of mass manufacturing in a semi- or fully-automated assembly line, Netsity proposes artificial intelligence based data analysis / classification, system control / monitoring, and design / performance optimization for fuel cells integrated with various physics-informed modelling techniques, by capturing data relating to temperature, pressure, humidity and flow rate, current and voltage data during the manufacturing process or operation of a fuel cell.

White Paper Abstract

Fuel cells major obstacles in its wide spread adoption are high costs, use of expensive materials & coatings, lack of mass-production technologies for achieving economies of scale, and difficulties in predicting the performance and durability of individual cells, or integrated stacks, and complete fuel cell systems with all its sub-systems. The underlying behaviour in cell performance and its manufacturing process is usually described by the principles of electrochemistry and thermodynamics, which are often difficult to model mathematically, resulting in labor-driven, error- prone process with high rate of defects, sub-optimal materials, and less-than-desirable electrochemical performance. In this white paper, we have attempted to look at several key aspects of fuel cell design, operational control, material development, and manufacturing process control, with an aim to find cost-effective solutions through machine learning, artificial intelligence and data analysis techniques, which have received increasing attention recently. Machine learning models have unique advantages in running simulations, as they require no prior knowledge, especially of the complex coupled transport and electrochemical processes occurring in fuel cell operation.

Published On: April 2021

White Paper Topics

The white paper focusses on different fuel cell technologies including Polymer Electrolyte Membrane Fuel Cells (PEMFC) and Solid Oxide Fuel Cells (SOFC) with bio-fuels such as green hydrogen, blue hydrogen with CCUS, green ammonia, green methanol or ethanol.

  • Fuel Cell manufacturing
  • Fuel Cell stack manufacturing
  • Fuel Cell system performance
  • Durability & efficiency of Fuel Cell system
  • Fuel Cell materials, coatings, components including R&D
  • Fuel Cell system design
  • Other aspects of Fuel Cell systems
White Paper References
  1. PEM Fuel Cell Voltage Neural Control Based on Hydrogen Pressure Regulation. Andrés Morán-Durán , Albino Martínez-Sibaja, José Pastor Rodríguez-Jarquin, Rubén Posada-Gómez and Oscar Sandoval González
  2. Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology. Yun Wanga, Bongjin Seoa, Bowen Wangb, Nada Zamelc, Kui Jiaob, Xavier Cordobes Adroherd
  3. Optimization of Component Sizing for a Fuel Cell-Powered Truck to Minimize Ownership Cost. Kyuhyun Sim , Ram Vijayagopal, Namdoo Kim and Aymeric Rousseau
  4. Challenges and developments of automotive fuel cell hybrid power system and control. Jinwu GAO, Meng LI2, Yunfeng HU2, Hong CHEN2 and Yan MA2
  5. Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries. Andrea Gayon-Lombardo1, Lukas Mosser2, Nigel P. Brandon1 and Samuel J. Cooper
  6. Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation. Haoran Xua, Jingbo Mab, Peng Tanc, Bin Chend, Zhen Wue, Yanxiang Zhangb, Huizhi Wangf, Jin Xuana, Meng Ni
  7. Covalency competition dominates the water oxidation structure–activity relationship on spinel oxides. Yuanmiao Sun, Hanbin Liao, Jiarui Wang, Bo Chen, Shengnan Sun, Samuel Jun Hoong Ong, Shibo Xi, Caozheng Diao, Yonghua Du, Jia-Ou Wang, Mark B. H. Breese , Shuzhou Li , Hua Zhang and Zhichuan J. Xu
  8. Performance Prediction of Proton Exchange Membrane Fuel Cells (PEMFC) Using Adaptive Neuro Inference System (ANFIS) Tabbi Wilberforce and Abdul Ghani Olabi
  9. Machine learning for guiding high-temperature PEM fuel cells with greater power density. Authors Luis A. Briceno-Mena, Gokul Venugopalan, Jose ́ A. Romagnoli, Christopher G. Arges
  10. Improving Fuel Cell Efficiency Through Machine Learning Techniques. Author Gary Elinoff
  11. Overcoming the Challenges for a Mass Manufacturing Machine for the Assembly of PEMFC. Stacks Sebastian Porstmann, Thomas Wannemacher and Thilo Richter
  12. Manufacturing Cost Analysis of PEM Fuel Cell Systems for 5- and 10-kW Backup Power Applications. By Battelle Memorial Institute
  13. Manufacturing cost analysis of 1 kw and 5 kw solid oxide fuel cell (sofc) for auxilliary power applications. By Battelle Memorial Institute
  14. Comparison of Fuel Cell Technologies. By Office of Energy Efficiency & Renewable Energy at US Department of Energy
  15. A comprehensive comparison of state-of-the-art manufacturing methods for fuel cell bipolar plates including anticipated future industry trends. S. Porstmann a, T. Wannemacher, W.-G. Drossel
  16. Challenges in Fabricating Solid Oxide Fuel Cell Stacks for Portable Applications: A Short Review. Nor Fatina Raduwan, Andanastuti Muchtar, Mahendra Rao Somalu, Nurul Akidah Baharuddin, Muhammed Ali SA
  17. Emerging Manufacturing Technologies for Fuel Cells and Electrolyzers. Ahmad Mayyas, Margaret Mann
  18. Machine Learning in Additive Manufacturing: A Review. Lingbin Meng, Brandon Mcwilliams, William Jarosinski, Hye-Yeong Park, Yeon-Gil Jung, Jehyun Lee and Jing Zhang
  19. Solid oxide fuel cell interconnect design optimization considering the thermal stresses. Min Xu, Tingshuai Li, Ming Yang, Martin Andersson
  20. Processing technologies for sealing glasses and glass-ceramics. Araceli de Pablos-Martín, Sonia Rodríguez-López, Maria J. Pascual
  21. Solid Oxide Fuel Cells (SOFC) by Dr Waldemar Bujalski
  22. Analysis of manufacturing processes for metallic and composite bipolar plates. Sebastian Porstmann, Allan Christian Petersen and Thomas Wannemacher
  23. A Total Cost of Ownership Model for Solid Oxide Fuel Cells in Combined Heat and Power and Power- Only Applications. Roberto Scataglini, Ahmad Mayyas, Max Wei, Shuk Han Chan, Timothy Lipman, David Gosselin, Anna D’Alessio, Hanna Breunig, Whitney G. Colella, and Brian D. James
  24. Systems Analysis of Solid Oxide Fuel Cell Plant Configurations. Gregory A. Hackett, Ph.D. NETL Research and Innovation Center
  25. Manufacturing Cost and Installed Price Analysis of Stationary Fuel Cell Systems. Brian D. James, Daniel A. DeSantis
  26. Study on Value Chain and Manufacturing Competitiveness Analysis for Hydrogen and Fuel Cells Technologies. FCH contract 192
  27. Report on Large Scale Manufacturing Strategy for Solid Oxide Fuel Cells (SOFC). By ComSos Co-funded by the European Commission within the H2020 Programme the Fuel Cells and Hydrogen 2 Joint Undertaking Grant Agreement no: 779481. Authour Markus Münch, Sunfire GmbH
  28. Fuel Cell Handbook (Seventh Edition) By EG&G Technical Services, Inc. Under Contract No. DE-AM26-99FT40575, U.S. Department of Energy, Office of Fossil Energy National Energy Technology Laboratory
  29. Benchmarking the expected stack manufacturing cost of next generation, intermediate-temperature protonic ceramic fuel cells with solid oxide fuel cell technology. Alexis Dubois, Sandrine Ricote, Robert J. Braun
  30. MEA manufacturing using an additive manufacturing process to deposit a catalyst pattern in an MEA and its impact on cost reduction. N. P. Kulkarni, T. E. Sparks, G. Tandra, F. W. Liou
  31. Fuel Cell MEA Manufacturing R&D. By Michael Ulsh, National Renewable Energy Laboratory
  32. Green and Low-Cost Membrane Electrode Assembly for Proton Exchange Membrane Fuel Cells: Effect of Double-Layer Electrodes and Gas Diffusion Layer. M. H. Gouda, Mohamed Elnouby, Andrew N. Aziz, M. Elsayed Youssef, D. M. F. Santos and Noha A. Elessawy
  33. A novel approach to fabricate membrane electrode assembly by directly coating Nafion ionomer on catalyst layers for proton exchange membrane fuel cells. Cheng Yang, Ning Han, Yajun Wang, Xiao-Zi Yuan, Jiaoyan Xu, Henghui Huang, Jiantao Fan, Hui Li, and Haijiang Wang
  34. Analysis and modeling of a membrane electrode assembly in a proton exchange membrane fuel cell. Mehmet F. Orhan , Kenan Saka, and Huseyin Kahraman
  35. Bipolar Plate Cost and Issues at High Production Rate Brian D. James. Jennie M. Huya-Kouadio. Cassidy Houchins. DOE Workshop on Research and Development Needs for Bipolar Plates for PEM Fuel Cell Technologies
  36. Proton Exchange Membrane Fuel Cell Stack Design Optimization Using an Improved Jaya Algorithm. Uday K. Chakraborty
  37. New Perspectives on Fuel Cell Technology: A Brief Review. Norazlianie Sazali, Wan Norharyati Wan Salleh, Ahmad Shahir Jamaludin, and Mohd Nizar Mhd Razali
  38. Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology. Yun Wang, Bongjin Seo, Bowen Wang, Nada Zamel, Kui Jiao, Xavier Cordobes Adroher
  39. Performance improvement by temperature control of an open-cathode pem fuel cell system. S. Strahl, A. Husar, P. Puleston, J. Riera
  40. Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation.  Xu Haorana, Ma Jingbo, Tan Peng, Chen Bin, Wu Zhen, Zhang Yanxiang, Wang Huizhi, Xuan Jin, Ni Meng
  41. Electrolyte materials for intermediate-temperature solid oxide fuel cells. Huangang Shia, Chao Su, Ran Ran, Jiafeng Cao, Zongping Shao