期刊
JOURNAL OF POWER SOURCES
卷 193, 期 2, 页码 699-705出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpowsour.2009.04.022
关键词
Solid oxide fuel cell (SOFC); Takagi-Sugeno (T-S) fuzzy model; Model predictive control (MPC)
Thermal management of a solid oxide fuel cell (SOFC) stack essentially involves control of the temperature within a specific range in order to maintain good performance of the stack. In this paper, a nonlinear temperature predictive control algorithm based on an improved Takagi-Sugeon (T-S) fuzzy model is presented. The improved T-S fuzzy model can be identified by the training data and becomes a predictive model. The branch-and-bound method and the greedy algorithm are employed to set a discrete optimization and an initial upper boundary, respectively. Simulation results show the advantages of the model predictive control (MPC) based on the identified and improved T-S fuzzy model for an SOFC stack. (C) 2009 Elsevier B.V. All rights reserved.
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