A novel SOFC system control strategy has been developed for rapid load following. The strategy was motivated from the performance of a baseline control strategy developed from control concepts in the literature. The basis for the fuel cell system control concepts are explained by a simplified order of magnitude time scale analysis. The control concepts are then investigated in a detailed quasi-two-dimensional integrated dynamic system model that resolves the physics of heat transfer, chemical kinetics, mass convection and electrochemistry within the system.The baseline control strategy is based on the standard operating method of constant utilization with no control of the combustor temperature. Simulation indicates that with this control strategy large combustor transients can take place during load transients because the fuel flow to the combustor increases faster than the air flow. To alleviate this problem, a novel control structure that maintains the combustor temperature within acceptable ranges without any supplementary hardware was introduced. The combustor temperature is controlled by manipulating the current to change the combustor inlet stoichiometry. The load following capability of SOFC systems is inherently limited by anode compartment fuel depletion during the time of fuel delivery delay. This research indicates that future SOFC systems with proper system and control configurations can exhibit excellent load following characteristics.
Current control systems regulate the behavior of dynamic systems by reacting to noise and unexpected disturbances as they occur. To improve the performance of such control systems, experience from iterative executions can be used to anticipate recurring disturbances and proactively compensate for them. This paper presents an algorithm that exploits data from previous repetitions in order to learn to precisely follow a predefined trajectory. We adapt the feed-forward input signal to the system with the goal of achieving high tracking performance-even under the presence of model errors and other recurring disturbances. The approach is based on a dynamics model that captures the essential features of the system and that explicitly takes system input and state constraints into account. We combine traditional optimal filtering methods with state-of-theart optimization techniques in order to obtain an effective and computationally efficient learning strategy that updates the feed-forward input signal according to a customizable learning objective. It is possible to define a termination condition that stops an execution early if the deviation from the nominal trajectory exceeds a given bound. This allows for a safe learning that gradually extends the time horizon of the trajectory. We developed a framework for generating arElectronic supplementary material The online version of this article (bitrary flight trajectories and for applying the algorithm to highly maneuverable autonomous quadrotor vehicles in the ETH Flying Machine Arena testbed. Experimental results are discussed for selected trajectories and different learning algorithm parameters.
Creep Contact analysis a b s t r a c tIntricate relationships between mechanical and electrochemical degradation aspects likely affect the durability of solid oxide fuel cell stacks. This study presents a modelling framework that combines thermo-electrochemical models including degradation and a contact thermo-mechanical model that considers rate-independent plasticity and creep of the components materials and the shrinkage of the nickel-based anode during thermal IntroductionThe end of operation of a solid oxide fuel cell (SOFC) stack ultimately occurs due to the loss of structural integrity of one or several of the cells, as highlighted by several short-stack experiments, e.g [1e4]. We believe this is the result of the accumulation during operation, of physico-chemical alterations inducing a weakening of the materials and interfaces, of plastic and creep deformations, and of the modification of the temperature profile, due to the degradation of the electrochemical performance of the cells. Mechanical issues do not, however, exclusively occur after prolonged use. Inappropriate control during start-up and shut-down and/or following of the electrical power demand, harsh characterisation procedures and thermal cycling can induce discrete failures [5,6]. Despite the evidence of mechanical issues in SOFCs, which are experienced even during laboratory button cell tests, this topic is still receiving limited attention. Efforts are seen as standalone tasks, owing to the different experimental and modelling techniques that are required to gather the essential information, whereas mechanical failures in SOFCs are likely intricately related to chemical and electrochemical aspects.The central component in a stack is the membrane electrode assembly (MEA). As for any multilayered system made of brittle materials, the MEA is prone to failures related to residual * Corresponding author. Tel.: þ41 21 693 35 05.E-mail address: arata.nakajo@epfl.ch (A. Nakajo).Available online at www.sciencedirect.com journal h om epa ge: www.elsev ier.com/locate/he i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 7 ( 2 0 1 2 ) 9 2 6 9 e9 2 8 6
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