Description
A system has been developed to enable the targeted down-selection of an extensive database of metal hydrides to identify the most promising materials for use in thermal systems. The materials’ database contains over 300 metal hydrides with various physical and thermodynamic properties included for each material. Submodels for equilibrium pressure, thermophysical data, and default properties are used to predict the behavior of each material within the given system. The application used at this time is a stationary combined heat and power system containing a hightemperature proton exchange membrane (PEM) fuel cell, a hot water tank, and two metal hydride beds used as a heat pump to increase the efficiency of a natural gas system. The targeted down-selection for this system focuses on the system’s coefficient of performance (COP) for each potential pair and the corresponding sensitivity of the COP and has been used to identify the top 20 pairs, with COPs >1.3, for use in this application.
Keywords
metal hydride thermal systems, hydride property database, thermodynamics, metal hydride toolbox, metal hydride heat pump
DOI
10.5703/1288284315541
Included in
Metal Hydride Component Design (MHy-CoDe) Tool for the Selection of Hydrides in Thermal Systems
A system has been developed to enable the targeted down-selection of an extensive database of metal hydrides to identify the most promising materials for use in thermal systems. The materials’ database contains over 300 metal hydrides with various physical and thermodynamic properties included for each material. Submodels for equilibrium pressure, thermophysical data, and default properties are used to predict the behavior of each material within the given system. The application used at this time is a stationary combined heat and power system containing a hightemperature proton exchange membrane (PEM) fuel cell, a hot water tank, and two metal hydride beds used as a heat pump to increase the efficiency of a natural gas system. The targeted down-selection for this system focuses on the system’s coefficient of performance (COP) for each potential pair and the corresponding sensitivity of the COP and has been used to identify the top 20 pairs, with COPs >1.3, for use in this application.