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Optimized parameter estimation of a PEMFC model based on improved Grass Fibrous Root Optimization Algorithm

تقدير معلمات محسّن لنموذج PEMFC بناءً على خوارزمية تحسين الجذر الليفي العشب المحسنة
Authors: Haibing Guo; Hai Tao; Sinan Q. Salih; Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬;

Optimized parameter estimation of a PEMFC model based on improved Grass Fibrous Root Optimization Algorithm

Abstract

Cet article présente une nouvelle méthodologie optimale pour l'identification des paramètres d'une pile à combustible à membrane polymère de 50 kW (PEMFC) basée sur le modèle économique-fonctionnel. L'objectif de l'étude est d'estimer de manière optimale les paramètres du système de sorte que le coût total minimum ait été nécessaire pour la construction de la cheminée. Le coût total ici est la somme du coût de la pile à combustible et de ses auxiliaires en tenant compte du coefficient stœchiométrique de l'air et de l'hydrogène, de la pression du système, de la densité de courant et de la température du système. Pour résoudre le problème de minimisation, un modèle nouvellement modifié de l'algorithme d'optimisation de la racine fibreuse de l'herbe (MGRA) a été présenté. Les résultats finaux sont comparés à plusieurs algorithmes bien connus pour indiquer l'efficacité du système et la fiabilité du système vis-à-vis de différents paramètres a été indiquée en appliquant une analyse de sensibilité.

Este documento presenta una nueva metodología óptima para la identificación de parámetros de una celda de combustible de membrana polimérica (PEMFC) de 50 kW basada en el modelo económico-funcional. El objetivo del estudio es la estimación óptima de los parámetros del sistema de modo que se haya necesitado el coste total mínimo para la construcción de la pila. El coste total aquí es la suma del coste de la pila de pilas de combustible y sus auxiliares considerando el coeficiente estequiométrico de aire e hidrógeno, la presión del sistema, la densidad de corriente y la temperatura del sistema. Para resolver el problema de minimización, se ha presentado un modelo recientemente modificado del Algoritmo de Optimización de Raíz Fibrosa de Hierba (MGRA). Los resultados finales se comparan con algunos algoritmos bien conocidos para indicar la eficiencia del sistema y la fiabilidad del sistema hacia diferentes parámetros se ha indicado mediante la aplicación de análisis de sensibilidad.

This paper presents a new optimal methodology for parameter identification of a 50 kW polymer membrane fuel cell (PEMFC) based on the economical–functional model. The objective of the study is to optimal estimation of the system parameters such that the minimum total cost has been needed for the stack construction. The total cost here is the sum of the fuel cell stack cost and its auxiliaries by considering air and hydrogen stoichiometric coefficient, system pressure, the current density, and the system temperature. For solving the minimization problem, a newly modified model of the Grass Fibrous Root Optimization Algorithm (MGRA) has been presented. Final results are compared with some several well-known algorithms to indicate the system efficiency and the reliability of the system toward different parameters has been indicated by applying sensitivity analysis.

تقدم هذه الورقة منهجية مثالية جديدة لتحديد المعلمات لخلية وقود غشاء البوليمر بقدرة 50 كيلو واط (PEMFC) بناءً على النموذج الاقتصادي الوظيفي. الهدف من الدراسة هو التقدير الأمثل لمعلمات النظام بحيث يكون الحد الأدنى للتكلفة الإجمالية مطلوبًا لبناء المكدس. التكلفة الإجمالية هنا هي مجموع تكلفة مكدس خلايا الوقود وملحقاته من خلال النظر في معامل التكافؤ للهواء والهيدروجين وضغط النظام وكثافة التيار ودرجة حرارة النظام. لحل مشكلة التقليل، تم تقديم نموذج معدل حديثًا لخوارزمية تحسين الجذور الليفية العشبية (MGRA). تتم مقارنة النتائج النهائية مع بعض الخوارزميات المعروفة للإشارة إلى كفاءة النظام وقد تمت الإشارة إلى موثوقية النظام تجاه المعلمات المختلفة من خلال تطبيق تحليل الحساسية.

Keywords

Stack (abstract data type), FOS: Mechanical engineering, Engineering, Fuel cells, Electrochemically–mechanically​ model, Energy, ddc:330, Minification, Physics, Mathematical optimization, Measure (data warehouse), Power (physics), Sensitivity (control systems), Programming language, Algorithm, Reliability (semiconductor), Physical Sciences, Polymer membrane fuel cell, Electrical engineering. Electronics. Nuclear engineering, Sensitivity analysis, Parameter identification, Lithium-ion Battery Management in Electric Vehicles, Quantum mechanics, Chemical engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Electrical and Electronic Engineering, System identification, PEM Fuel Cells, Data mining, FOS: Chemical engineering, Electrochemically-mechanically model, Renewable Energy, Sustainability and the Environment, Electronic engineering, Proton exchange membrane fuel cell, Grass Fibrous Root Optimization Algorithm, Fuel Cell Durability, Computer science, TK1-9971, Fuel Cell Membrane Technology, Automotive Engineering, Electrocatalysis for Energy Conversion, Mathematics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
gold