کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5148416 1497369 2017 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Brain-inspired computational paradigm dedicated to fault diagnosis of PEM fuel cell stack
موضوعات مرتبط
مهندسی و علوم پایه شیمی الکتروشیمی
پیش نمایش صفحه اول مقاله
Brain-inspired computational paradigm dedicated to fault diagnosis of PEM fuel cell stack
چکیده انگلیسی
Features such as low greenhouse-gas emission, high energy efficiency and operating stability make fuel cell (FC) an attractive power source for a wide variety of applications. Nevertheless, to achieve its commercialization, durability and reliability remain big challenges. This work aims at developing an efficient data-driven fault detection and identification methodology through the use of a recently proposed brain-inspired computational paradigm, Reservoir Computing (RC). The considered “Reservoir” is made of a particular class of complex dynamics emulating a virtual neural network, and modeled by a nonlinear delay equation. This original and experimentally compatible approach indeed demonstrated recently excellent performances on complex nonlinear problems such as classification and prediction tasks. In this work, a first attempt is made to introduce the RC method into the field of FC diagnosis. Targeted fault types include CO poisoning, low air flow rate, defective cooling and natural degradation. Experimental results show the simplicity and efficiency of RC method to discriminate the abovementioned health states. Moreover, the influence of four key RC parameters and also of the learning database is investigated in order to explore the possibility of further facilitating and generalizing the RC approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Hydrogen Energy - Volume 42, Issue 8, 23 February 2017, Pages 5410-5425
نویسندگان
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