By Topic

Adaptive State Estimation of a PEM Fuel Cell

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Vepa, R. ; Sch. of Eng. & Mater. Sci., Queen Mary, Univ. of London, London, UK

In this paper, the adaptive method is coupled with the unscented Kalman filter (UKF) and is used to estimate the states of polymer electrolyte membrane fuel cell. Our aim is to establish the superiority of the adaptive UKF over the standard UKF with no adaptation of the process noise covariance matrix. For purposes of estimation certain internal states such as the liquid water mass in the anode and cathode channel, liquid water volumes and pressures in the gas diffusion layers, and the stack temperature are assumed to have reached steady state. When this is done and fuel-cell measurements are made of the stack voltage, the relative humidity in the anode and cathode channels, the stack temperature, and the stack current, one can set up a nonlinear observer model. The model facilitates the estimation of the states and key parameters of fuel-cell stack in real time. The estimated states converge and subsequent simulations with these states incorporated into the model demonstrate good performance characteristics, such as the stack voltage and output power. By comparing the estimated stack voltage with and without adaptation it is shown that the adaptive state estimation method is superior to the case without adaptation.

Published in:

Energy Conversion, IEEE Transactions on  (Volume:27 ,  Issue: 2 )