An adaptive non-linear observer for the estimation of temperature distribution in the planar solid oxide fuel cell
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Minimising the thermal gradients is extremely important in a planar solid oxide fuel cell (SOFC) forimproving the cell life. The estimation of the temperature distribution in the cell is necessary to achievethis objective through suitable control, since they are not generally measurable. In this work, we havedesigned a non-linear adaptive observer for estimating the temperatures inside the hydrogen fed planarSOFC. The observer design is based on a lumped parameter model of the SOFC. The stability of theproposed 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 cell current. The adaptive observer presented is valid for a wide operating range, requires fewer variables to be measured, and is robust to fluctuations in the inlet flows.
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Simultaneous estimation of states and inputs in a planar solid oxide fuel cell using nonlinear adaptive observer designVijay, Periasamy; Tade, Moses; Ahmed, K.; Utikar, Ranjeet; Pareek, Vishnu (2013)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 ...
Hosseini, Shahin; Danilov, Valery; Vijay, Periasamy; Tade, Moses (2011)Models of different complexity are required in the iterative process of designing a solid oxide fuel cell (SOFC). Models having less complexity and computational dexterity are the ideal ones at the early stages. This work ...
Periasamy, Vijay ; Tade, Moses ; Shao, Zongping (2019)© 2019 Elesevier Monitoring and fault diagnosis can play a major role in improving the reliability of Solid Oxide Fuel Cell (SOFC) systems. Due to complex interactions between the variables, quantitative model based methods ...