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 ne...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.展开更多
Electrochemical impedance spectroscopy (EIS) is widely used in fuel cell impedance analysis. However, for ohmic resistance (R Ω), EIS has some disadvantages such as long test period and complex data analysis with equ...Electrochemical impedance spectroscopy (EIS) is widely used in fuel cell impedance analysis. However, for ohmic resistance (R Ω), EIS has some disadvantages such as long test period and complex data analysis with equivalent circuits. Therefore, the current interruption method is explored to measure the value of RΩ in direct methanol fuel cells (DMFC) at different temperatures and current densities. It is found that RΩ decreases as temperature increase, and decreases initially and then increases as current density increases. These results are consistent with those measured by the EIS technique. In most cases, the ohmic resistances with current interruption (R iR ) are larger than those with EIS (R EIS ), but the difference is small, in the range from –0.848% to 5.337%. The errors of R iR at high current densities are less than those of R EIS . Our results show that the R iR data are reliable and easy to obtain in the measurement of ohmic resistance in DMFC.展开更多
Supported PtRu/C catalysts used in direct methanol fuel cells (DMFCs) were prepared by a new modified polyol method. Transmission electron microscopy (TEM), X-ray diffraction (XRD) and cyclic voltammograms (CVs) were ...Supported PtRu/C catalysts used in direct methanol fuel cells (DMFCs) were prepared by a new modified polyol method. Transmission electron microscopy (TEM), X-ray diffraction (XRD) and cyclic voltammograms (CVs) were carried out to characterize the morphology, composition and the electrochemical properties of the PtRu/C catalyst. The results revealed that the PtRu nanoparticles with small average particle size (≈2.5 nm), and highly dispersed on the carbon support. The PtRu/C catalyst exhibited high catalytic activity and anti poisoned performance than that of the JM PtRu/C. It is imply that the modified polyol method is efficient for PtRu/C catalyst preparation.展开更多
Platinum/Carbon XC72R （Pt/C） nanocomposite was synthesized in-situ by polyol method. Precursor of hexahydrated chloroplatinic acid H2PtCI6-6H2O was reduced by EG （ethylene glycol） so as to form Pt nanoparticles wh...Platinum/Carbon XC72R （Pt/C） nanocomposite was synthesized in-situ by polyol method. Precursor of hexahydrated chloroplatinic acid H2PtCI6-6H2O was reduced by EG （ethylene glycol） so as to form Pt nanoparticles which were deposited on the surface of carbon. Pt/C composites （treated or untreated carbon） were synthesized at pH - 6.5 and pH = 11. The XRD pattern of Pt/C showed peaks assigned to the crystalline structure of Pt and carbon. TEM images showed that Pt nanoparticles on carbon were ultrafine spheres and the particles obtained sizes from 2 to 6 nm which are mostly concentrated on size of 3 nm. The electrocatalytic activity of Pt/C catalysts toward methanol oxidation was examined by CV （cyclic voltammetry）. Pt/treated XC72R （pH = 11） at potential （0.69 V） exhibited better electroactivity （628 mA/mg Pt）.展开更多
Aiming at on-line controlling of Direct Methanol Fuel Cell （DMFC） stack, an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system. In the modeling process, an A...Aiming at on-line controlling of Direct Methanol Fuel Cell （DMFC） stack, an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system. In the modeling process, an Adaptive Neural Fuzzy Inference System （ANFIS） identification model of DMFC stack temperature is developed based on the input-output sampled data, which can avoid the internal complexity of DMFC stack. In the controlling process, with the network model trained well as the reference model of the DMFC control system, a novel fuzzy genetic algorithm is used to regulate the parameters and fuzzy rules of a neural fuzzy controller. In the simulation, compared with the nonlinear Proportional Integral Derivative （PID） and traditional fuzzy algorithm, the improved neural fuzzy controller designed in this paper gets better performance, as demonstrated by the simulation results.展开更多
基金Project supported by the National High-Technology Research and Development Program Foundation of China(Grant No.2003AA517020)
文摘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.
基金Supported by the National High Technology Research and Development Program of China （2007AA05Z150） the National Natural Science Foundation of China （50911140287 50973055）
文摘Electrochemical impedance spectroscopy (EIS) is widely used in fuel cell impedance analysis. However, for ohmic resistance (R Ω), EIS has some disadvantages such as long test period and complex data analysis with equivalent circuits. Therefore, the current interruption method is explored to measure the value of RΩ in direct methanol fuel cells (DMFC) at different temperatures and current densities. It is found that RΩ decreases as temperature increase, and decreases initially and then increases as current density increases. These results are consistent with those measured by the EIS technique. In most cases, the ohmic resistances with current interruption (R iR ) are larger than those with EIS (R EIS ), but the difference is small, in the range from –0.848% to 5.337%. The errors of R iR at high current densities are less than those of R EIS . Our results show that the R iR data are reliable and easy to obtain in the measurement of ohmic resistance in DMFC.
文摘Supported PtRu/C catalysts used in direct methanol fuel cells (DMFCs) were prepared by a new modified polyol method. Transmission electron microscopy (TEM), X-ray diffraction (XRD) and cyclic voltammograms (CVs) were carried out to characterize the morphology, composition and the electrochemical properties of the PtRu/C catalyst. The results revealed that the PtRu nanoparticles with small average particle size (≈2.5 nm), and highly dispersed on the carbon support. The PtRu/C catalyst exhibited high catalytic activity and anti poisoned performance than that of the JM PtRu/C. It is imply that the modified polyol method is efficient for PtRu/C catalyst preparation.
文摘Platinum/Carbon XC72R （Pt/C） nanocomposite was synthesized in-situ by polyol method. Precursor of hexahydrated chloroplatinic acid H2PtCI6-6H2O was reduced by EG （ethylene glycol） so as to form Pt nanoparticles which were deposited on the surface of carbon. Pt/C composites （treated or untreated carbon） were synthesized at pH - 6.5 and pH = 11. The XRD pattern of Pt/C showed peaks assigned to the crystalline structure of Pt and carbon. TEM images showed that Pt nanoparticles on carbon were ultrafine spheres and the particles obtained sizes from 2 to 6 nm which are mostly concentrated on size of 3 nm. The electrocatalytic activity of Pt/C catalysts toward methanol oxidation was examined by CV （cyclic voltammetry）. Pt/treated XC72R （pH = 11） at potential （0.69 V） exhibited better electroactivity （628 mA/mg Pt）.
文摘Aiming at on-line controlling of Direct Methanol Fuel Cell （DMFC） stack, an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system. In the modeling process, an Adaptive Neural Fuzzy Inference System （ANFIS） identification model of DMFC stack temperature is developed based on the input-output sampled data, which can avoid the internal complexity of DMFC stack. In the controlling process, with the network model trained well as the reference model of the DMFC control system, a novel fuzzy genetic algorithm is used to regulate the parameters and fuzzy rules of a neural fuzzy controller. In the simulation, compared with the nonlinear Proportional Integral Derivative （PID） and traditional fuzzy algorithm, the improved neural fuzzy controller designed in this paper gets better performance, as demonstrated by the simulation results.
