Abstract
The performance of fuel cells and the vehicle applications they are embedded into depends on a delicate balance of the correct temperature, humidity, reactant pressure, purity and flow rate. This paper successfully investigates the problem related to flow control with implementation on a single cell membrane electrode assembly (MEA). This paper presents a systematic approach for performing system identification using recursive least squares identification to account for the non-linear parameters of the fuel cell. Then, it presents a fuzzy controller with a simplified rule base validated against real time results with the existing flow controller which calculates the flow required from the stoichiometry value.
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Jonathan G Williams received his B. Eng. and M. Eng. degrees in mechatronic engineering with the 1st Class Honours at the University of Glamorgan in 2005. Recently, he has been studying for his Ph. D. in “advanced control strategies for improvements in fuel cell system performance” with 3 conference papers and 2 journal publications related to this topic in publication. He is a research student and part time project manager at the University of Glamorgan, UK. He is also a steering committee member of the Welsh Mechatronics Forum, and advisor to Welsh Assembly Government and the Welsh Automotive Forum on energy efficiency and renewable power systems. Currently, he also manages two advanced power-train projects related to his fuel cell research, funded by the Energy Saving Trust and Knowledge Exploitation Fund. Both projects will deliver unique all electric driven vehicles, utilising a unique tribrid power-train. This is based on the control of a unique battery technology along with fuel cell and ultra-capacitors to delivery a real alternative to traditional internal combustion. For his research portfolio, he was awarded the prestigious Welsh Livery Guild in 2007, and also awarded the Welsh Nexus fund to represent his research topics at two international conferences in 2007. During his undergraduate studies, he was also awarded the Pilkington Prize for his project management skills related to his studies, the M. Eng. Student of the year award, and highest overall marking for his year group. He also has established industrial links with over 45 companies, nationally, and internationally in the automotive sector, including Lotus, Pro-Drive and Zytek. He also worked for Robert Bosch as a production manager and was responsible for design and installation of a new automated welding assembly line for alternators.
His research interests include non-linear modelling and predictive controller design, fuzzy and neural network controllers as well as classical control.
Guoping Liu received his B.Eng. and M. Eng. degrees in electrical and electronic engineering from the Central South University of Technology (now the Central South University) in China in 1982 and 1985, respectively, and his Ph.D. degree in control engineering from UMIST (now the University of Manchester) in the UK in 1992. He did postdoctoral research in the University of York in 1992–1993. He worked as a research fellow in the University of Sheffield in 1994. During 1996–2000, he was a senior engineer in GEC-Alsthom and ALSTOM, and then a principal engineer and a project leader in ABB ALSTOM Power. He was a senior lecturer in the University of Nottingham, UK, in 2000–2003. He has been a professor in the University of Glamorgan since 2004, a visiting professor of the Chinese Academy of Sciences since 2000, and a visiting professor of the Central South University since 1994. Currently, he is the chair of control engineering at the University of Glamorgan. He is a senior IEEE member and the general chair of the IEEE International Conference on Networking, Sensing and Control, 2007. He was awarded the Alexander von Humboldt Research Fellowship in 1992. He received the best paper prize for applications at the UKACC International Conference on Control in 1998. His paper was shortlisted for the best application prize at the 14th IFAC World Congress in 1999. He has worked more than 50 academic research and industrial technology projects. He has more than 300 publications on control systems. He authored or co-authored 6 books.
His research interests include networked control systems, modelling and control of fuel cells, advanced control of industrial systems, nonlinear system identification and control, and multi-objective optimisation and control.
Senchun Chai received his M. Sc. degree in the School of Automation Control, Beijing Institute of Technology, and the Ph.D. degree from the School of Electronics, University of Glamorgan, UK, in 2007. He is was research fellow in the Faculty of Advanced Technology at the University of Glamorgan in 2004. Currently, he works as a research fellow on a European FP7 project for improvements in rotary drier for varying processes.
His research interests include network predictive control and nonlinear system identification methods.
David Rees received his B. Sc. degree in electrical engineering from the University College, Swansea in 1967, and the Ph.D. degree in signal processing applied to composite frequency testing, awarded by the Council of National Academic Awards in 1976. He is currently an ex-associate head and director of research in the school of electronics at the University of Glamorgan, UK. His industrial experience includes five years with British Steel and two years with Imperial Chemical Industries. He is a fellow of the IET and a chartered engineer. He is a past chairman of the IEE Control Applications Committee and in 1996 was awarded the IEE F C Williams Premium Prize, which was the highest award of its computing and control division. He has published over 170 scientific papers, including contributing to a number of research monographs.
His research interests include system identification, modelling and control.
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Williams, J.G., Liu, G., Chai, S. et al. Intelligent control for improvements in PEM fuel cell flow performance. Int. J. Autom. Comput. 5, 145–151 (2008). https://doi.org/10.1007/s11633-008-0145-5
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DOI: https://doi.org/10.1007/s11633-008-0145-5