摘要
This paper introduced a novel self-adjustment of parameters of fuzzy neural networks. Then, the effects of cathode humidification temperature and anode flow rate on the performance of direct methanol fuel celI（DMFC） were described respectively. Two dynamic performance models of DMFC under the influences of cathode humidification temperature and anode flow rate were established separately based on fuzzy neural networks. The simulation results show the accuracy of the models established is satisfactory.
This paper introduced a novel self-adjustment of parameters of fuzzy neural net works.Then,the effects of cathode humidification temperature and anode flow rate on the performance of direct meth anol fuel cell(DMFC) were described respectively.Two dynamic performance models of DMFC under the influences of cat hode humidification temperature and anode flow rate were established separately based on fuzzy neural networks.The simula tion results show the accuracy of the models established is satisfactory.
