Simultaneous estimation of states and inputs in a planar solid oxide fuel cell using nonlinear adaptive observer design

Abstract

An adaptive nonlinear observer design for the planar solid oxide fuel cell (SOFC) is presented in this work. This observer is based on a lumped parameter model of the SOFC and it can simultaneously estimate the inputs and the states of the system. Considering the inputs as unknown parameters is advantageous because some of the input parameters are not practically measurable in a SOFC stack. The asymptotic stability of the proposed observer is proven using the Lyapunov function method and is based on the concept of input-to-state stability for cascaded systems. The simulations show that the developed observer can track the temperature and species concentration profiles in the planar SOFC during step changes in the input variables and can simultaneously predict the input variables. The adaptive observer presented is valid for a wide operating range, requires fewer variables to be measured, and is robust to fluctuations in the input variables.