Intelligent Machine Learning Analysis for Fuel Cell Operations

Murphy, R.W. ; Hoyt, W.A.

Oak Ridge National Laboratory

关键词: Efficiency;    Programming Languages;    32 Energy Conservation, Consumption, And Utilization;    Solid Oxide Fuel Cells;    Fortran;   

DOI  :  10.2172/940376
RP-ID  :  ORNL96-0431
RP-ID  :  DE-AC05-00OR22725
RP-ID  :  940376

美国|英语

来源: UNT Digital Library

【 摘 要 】

A performance computational model for a 100 kW nominal solid oxide fuel cell generator system is described. The calculational methods are based on the FORTRAN programming language. Comprehensive parameter input options are presented, and constraints are identified. Example reactant, electrical, and efficiency outputs are demonstrated over the relevant operating ranges. A sample calculated output display at nominal operating conditions is given.