Genetic Algorithm-based Modeling of PEM Fuel Cells Suitable for Integration in DC Microgrids
Genetic Algorithm-based Modeling of PEM Fuel Cells Suitable for Integration in DC Microgrids
- New search for: Kumar, Priya
- New search for: Kumar, Priya
- New search for: Kannaiah, Sathish Kumar
- New search for: Choudhury, Sashang Roy
- New search for: Rajasekar, Natarajan
Operating conditions such as temperature and pressure affect the fuel cell performance. Proton Exchange Membrane (PEM) fuel cells work at its maximum efficiency when it is operated within temperature limits. To improve the heat transfer properties of PEM fuel cells, nano coolants are added. Identification of a suitable combination of thermal conductivity, relative humidity, and parametric coefficients for performance assessment of PEM fuel cells in real time is mandatory. Conventional methods follow complex computations and trial and error procedure to model fuel cell without thermal management parameters. Hence, in this paper, the objective of parameter set identification is framed as an optimization problem and solved using Genetic Algorithm method. The performance of the proposed approach is evaluated for different test conditions and validated through simulation findings.
Document information
Genetic Algorithm-based Modeling of PEM Fuel Cells Suitable for Integration in DC Microgrids
Electric power components and systems ; 45 , 10
2017
Article (Journal)
English
PEMFC , Performance assessment , Coolants , Heat transfer , Computer simulation , Proton exchange membrane fuel cells , Genetic algorithms , Thermal conductivity , Relative humidity , Fuel cells , Automobile industry , Electric power grids , nano fluids , modeling of PEMFC , Thermal management , Product development , Parameter identification , Heat exchange , Fuels
Similar titles
Fuel-Optimal Strategies for Vehicle Supported Military Microgrids
| SAE Technical Papers | 2016
Optimal Dispatch Using Improved l-Based Genetic Algorithm Suitable for Utility Systems
| Online Contents | 2003