دانلود مقاله ISI انگلیسی شماره 42474
عنوان فارسی مقاله

مدیریت استرس حرارتی از یک سلول سوختی اکسید جامد با استفاده از کنترل پیش بینی شبکه عصبی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
42474 2013 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Thermal stress management of a solid oxide fuel cell using neural network predictive control
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy, Volume 62, 1 December 2013, Pages 320–329

کلمات کلیدی
جامد پیلسوختی اکسید - شبکه عصبی کنترل پیش بینی - دمای سلول لوله - تنش های حرارتی
پیش نمایش مقاله
پیش نمایش مقاله مدیریت استرس حرارتی از یک سلول سوختی اکسید جامد با استفاده از کنترل پیش بینی شبکه عصبی

چکیده انگلیسی

In SOFC (solid oxide fuel cell) systems operating at high temperatures, temperature fluctuation induces a thermal stress in the electrodes and electrolyte ceramics; therefore, the cell temperature distribution is recommended to be kept as constant as possible. In the present work, a mathematical model based on first principles is presented to avert such temperature fluctuations. The fuel cell running on ammonia is divided into five subsystems and factors such as mass/energy/momentum transfer, diffusion through porous media, electrochemical reactions, and polarization losses inside the subsystems are presented. Dynamic cell-tube temperature responses of the cell to step changes in conditions of the feed streams is investigated. The results of simulation indicate that the transient response of the SOFC is mainly influenced by the temperature dynamics. It is also shown that the inlet stream temperatures are associated with the highest long term start-up time (467 s) among other parameters in terms of step changes. In contrast the step change in fuel velocity has the lowest influence on the start-up time (about 190 s from initial steady state to the new steady state) among other parameters. A NNPC (neural network predictive controller) is then implemented for thermal stress management by controlling the cell tube temperature to avoid performance degradation by manipulating the temperature of the inlet air stream. The regulatory performance of the NNPC is compared with a PI (proportional–integral) controller. The performance of the control system confirms that NNPC is a non-linear-model-based strategy which can assure less oscillating control responses with shorter settling times in comparison to the PI controller.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.