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| Modelling and control PEMFC using fuzzy neural networks |
| SUN Tao, YAN Si-jia, CAO Guang-yi, ZHU Xin-jian |
| Fuel Cell Institute, Department of Automation, Shanghai Jiao Tong University, Shanghai 200030, China; Department of Applied Chemistry, Shanghai Normal University, Shanghai 200234, China |
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Abstract Proton exchange membrane generation technology is highly efficient, clean and considered as the most hopeful “green” power technology. The operating principles of proton exchange membrane fuel cell (PEMFC) system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model and control online. This paper first simply analyzes the characters of the PEMFC; and then uses the approach and self-study ability of artificial neural networks to build the model of the nonlinear system, and uses the adaptive neural-networks fuzzy infer system (ANFIS) to build the temperature model of PEMFC which is used as the reference model of the control system, and adjusts the model parameters to control it online. The model and control are implemented in SIMULINK environment. Simulation results showed that the test data and model agreed well, so it will be very useful for optimal and real-time control of PEMFC system.
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Received: 10 December 2004
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