Performance analysis and fuzzy neural networks modeling of direct methanol fuel cell
This paper introduces the effects of cell operating temperature, methanol concentration and airflow rate, respectively, on the performance of direct methanol fuel cell (DMFC). A novel method based on fuzzy neural networks identification technique is proposed to establish the performance model of DMFC. Three dynamic performance models of DMFC under the influences of cell operating temperature, methanol concentration, and airflow rate are identified and established separately.Simulation results show that modeling using fuzzy neural networks identification is satisfactory with high accuracy. It is applicable to DMFC control systems.
direct methanol fuel cell (DMFC)fuzzy neural networksDMFC control system
苗青、曹广益、朱新坚
展开 >
Institute of Fuel Cell, Department of Automation, Shanghai Jiaotong University, Shanghai 200030, P. R. China
direct methanol fuel cell (DMFC) fuzzy neural networks DMFC control system
NETL
NSTL
万方数据
