کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1294693 973633 2008 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic temperature modeling of an SOFC using least squares support vector machines
موضوعات مرتبط
مهندسی و علوم پایه شیمی الکتروشیمی
پیش نمایش صفحه اول مقاله
Dynamic temperature modeling of an SOFC using least squares support vector machines
چکیده انگلیسی
Cell temperature control plays a crucial role in SOFC operation. In order to design effective temperature control strategies by model-based control methods, a dynamic temperature model of an SOFC is presented in this paper using least squares support vector machines (LS-SVMs). The nonlinear temperature dynamics of the SOFC is represented by a nonlinear autoregressive with exogenous inputs (NARXs) model that is implemented using an LS-SVM regression model. Issues concerning the development of the LS-SVM temperature model are discussed in detail, including variable selection, training set construction and tuning of the LS-SVM parameters (usually referred to as hyperparameters). Comprehensive validation tests demonstrate that the developed LS-SVM model is sufficiently accurate to be used independently from the SOFC process, emulating its temperature response from the only process input information over a relatively wide operating range. The powerful ability of the LS-SVM temperature model benefits from the approaches of constructing the training set and tuning hyperparameters automatically by the genetic algorithm (GA), besides the modeling method itself. The proposed LS-SVM temperature model can be conveniently employed to design temperature control strategies of the SOFC.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Power Sources - Volume 179, Issue 2, 1 May 2008, Pages 683-692
نویسندگان
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