Abstract
PEMFC (proton exchange membrane fuel cell) Stack temperature control system is a strong-coupling system with characteristics of time-change, long-hysteresis, uncertainty and nonlinear. The dissertation studied PEMFC stack temperature control used by BP neural network controller which has a good control quality and a low degree of demand for model. In the Matlab platform, the model of the electric reactor temperature control system is established and compared with the traditional PID. It has been proved that BP neural network control system has very good robustness and control quality and it meet the demand of PEMFC stack temperature control system.
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