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Our research group focuses on the following special developments related to proton exchange membrane fuel cells:

1. Development of real time simulation algorithms for a better control of fuel cells
2. Elucidation of fuel cell transients and development of real-time parameter estimation techniques for in-field applications

Coat of arms of the Eötvös Loránd University

Real-time modelling

At a glance, fuel cells seem to be simpler devices than internal combustion engines (ICE), i.e., they have no moving parts, but the non-linear and coupled phenomena between the different subsystems make it hard to understand and control them in real time. There are three different approaches to build an adequate model of an FC system and develop an efficient control strategy:

1. Detailed FC models based on partial differential equations.
2. Steady-state FC system models based on experimental maps and look-up tables.
3. Dynamic FC system models that neglect spatial variations.

However, these are not real-time models, or the transient responses of FCs cannot be handled by using these approaches. Hence a control-oriented real-time model is needed. Such a model can be used for real-time parameter estimation for feedback control, or for more effective and energy-saving drive system. In this research, different non-linear numerical models of FCs are investigated, determining the speed, stability, accuracy and the conservation of basic qualitative properties. A new approach, the parameter scaling and operator splitting method are introduced to simulate FCs in real time.

Real-time parameter estimation

One of the aims of our work is to study the effectiveness of different parameter estimation techniques for proton exchange membrane fuel cells (PEMFC) under normal operating conditions. The procedure for the estimation of the real-time parameters is in good approximation meets the requirements imposed regarding such techniques, i.e., to obtain data without interrupting the functioning of the fuel cell and to be as simple as possible. In this approach, a fuel cell combined with a step-down voltage regulator system is analyzed, and the potential relaxation is used to determine the electrochemical properties of the PEMFC. The real-time determination of the state of health (SOH) of a functioning fuel cell and the optimization of the operating conditions are as important as novel materials. Usually, such investigations still require complicated experiments and instrumentations such as potentiostats, frequency analyzers and electrochemical impedance spectroscopy, and the regulations need time-consuming algorithms, i.e., these procedures cannot be applied in field operations. With the help of real-time parameter estimation, unwanted phenomena, such as catalyst poisoning, flooding or drying of the membrane, etc., can be monitored, and the working parameters of an FC can be quickly regulated.

Members of the group

• ELTE-TTK Department of Applied Analysis and Computational Mathematics

• ELTE-TTK Laboratory of Electrochemistry and Electroanalytical Chemistry

• Balázs B. Berkes
  Student, ELTE, Laboratory of Electrochemistry and Electroanalytical Chemistry
• Dr. István Faragó
  Associate professor, Head of the Department, ELTE, Department of Applied Analysis and Computational Mathematics
• Dr. Ágnes Havasi
  Assistant lecturer, ELTE, Department of Meteorology
• Dr. Róbert Horváth
  Associate professor, BME, Institute of Mathematics, Department of Analysis
• Tamás Horváth
  PhD student, ELTE, Department of Applied Analysis and Computational Mathematics
• Dr. Ferenc Izsák
  Assistant professor, ELTE, Department of Applied Analysis and Computational Mathematics
• Dr. György Inzelt
  Professor, Head of the Doctoral School in Chemistry, ELTE Laboratory of Electrochemistry and Electroanalytical Chemistry
• Ákos Kriston
  PhD student, ELTE, Laboratory of Electrochemistry and Electroanalytical Chemistry
• Dr. Péter Simon
  Associate professor, ELTE, Department of Applied Analysis and Computational Mathematics
• Tamás Szabó
  PhD student, ELTE, Department of Applied Analysis and Computational Mathematics