Identification of Nonlinear Multi Input Multi Output Model of PEM Fuel Cell Stack System
- Resource Type
- Conference
- Authors
- Soltanieh, Amin; Ogun, Oluwaseyi
- Source
- Electrical Engineering (ICEE), Iranian Conference on Electrical Engineering (ICEE), 2018 Iranian Conference on. :887-892 May, 2018
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Fuel cells
Mathematical model
MIMO communication
Atmospheric modeling
Correlation
Steady-state
Hydrogen
component
Proton Exchange Membrane Fuel Cell
PEM Fuel Cells1
Identification
Nonlinear Dynamical System
Nonlinear Control Systems
Recursive Least Squares
Instrumental Variable
Bilinear
Multi Input Multi Output
- Language
Fuel cells provide clean and efficient energy and recently there have been intense development by many companies in order to use in various applications (stationary or mobile). The performance, stability and robustness of electricity generation in these power sources are dependent on understanding and estimating the transient and steady state behavior of the fuel cell system. The goal of this project is to find a low order model and proper estimator for the multi input multi output (MIMO) nonlinear fuel cell stack system which can be used in control purposes in future studies. After analyzing transient state of fuel cell, the system is linearized about the operating range. Then a MIMO bilinear model is chosen among several ones and Recursive Least Squares (RLS) method is used to estimate MIMO bilinear model parameters. At the final stage, the measurement noise is added to the system, and instrumental variable (IV) method adopted for bilinear model is used to estimate the parameters and system simulation. This research is based on the data obtained by Matlab Simulation model by Dr. Pukrushpan [1]. In future studies data derived by the actual fuel cell stack system can be used.