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Book ChapterDOI

PEM Fuel Cell System Identification and Control

01 Jan 2018-pp 449-457

TL;DR: A mathematical model of a real-time PEMFC is obtained and its quality is assessed using various validation techniques and validation procedures like recursive least square algorithm, ARX and ARMAX were employed to assess the model.
Abstract: A model is an input–output mapping that suitably explains the behavior of a system. Model helps to analyze the functionality of the system and to design suitable controllers. System identification builds model from experimental data obtained by exciting the process with an input and observing its response at regular interval (Wibowo et al. in System identification of an interacting series process for real-time model predictive control, American Control Conference, pp. 4384–4389, 2009). Fuel cells (FC) systems are a potentially good clean energy conversion technology, and they have wide range of power generation applications. Classification of fuel cells is based on the fuel and the electrolyte type used. The proton exchange membrane fuel cells (PEMFC) are portable devices with superior performance and longer life. They act as a good source for ground vehicle applications. They also possess high power density and fast start-up time. In this work, mathematical model of a real-time PEMFC is obtained and its quality is assessed using various validation techniques. The model is obtained using system identification tool in MATLAB, and validation procedures like recursive least square algorithm, ARX and ARMAX were employed to assess the model. Controllers such as PI and PID were employed in order to achieve the desired load current by controlling the hydrogen flow rate. The values of the gain constant, integral time and derivative time were obtained using Cohen-Coon method. PI and PID control schemes were implemented using SIMULINK in MATLAB environment, and the system response was observed.
Citations
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Journal ArticleDOI
Dongmin Yu1, Dongmin Yu2, Yong Wang1, Yong Wang2  +4 moreInstitutions (3)
TL;DR: An optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for increasing their efficiency in the next designs of the proton exchange membrane fuel cell.
Abstract: Parameter identification of the proton exchange membrane fuel cell (PEMFC) is a good way of increasing their efficiency in the next designs. In this study, an optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for this purpose. The proposed algorithm is a hybrid algorithm based on a combination of two newly algorithms, the world cup optimization (WCO) and the fluid Search Optimization (FSO) algorithms. The proposed method is applied to improve the method efficiency for estimating the PEMFC model parameters. The method is then validated by four different operational conditions. The optimization algorithm efficiency is also analyzed by comparison with some popular algorithms. Simulation results showed that using the designed method gives higher accuracy forecast for the PEMFC model parameters.

82 citations


Journal ArticleDOI
Yan Cao, Yiqing Li, Geng Zhang, Kittisak Jermsittiparsert1  +1 moreInstitutions (1)
TL;DR: An improved version of seagull optimization algorithm for optimal parameter identification of the PEMFC stacks is presented and results show the algorithm’s superiority in terms of the solutions quality and the convergence speed.
Abstract: This study proposes an optimal model to design and simulate the proton exchange membrane fuel cell (PEMFC) systems. The purpose of this paper is to present an improved version of seagull optimization algorithm for optimal parameter identification of the PEMFC stacks. The new algorithm uses the Levy flight mechanism to give faster convergence rates. The sum of the squared error between the empirical values and achieved optimal model is analyzed based on two empirical PEMFC models including BCS 500-W and NedStack PS6. This analysis is performed to show the potential of the presented method by considering different conditions. Simulation results are compared with several optimization algorithms and show the algorithm’s superiority in terms of the solutions quality and the convergence speed.

72 citations


Journal ArticleDOI
TL;DR: A new improved version based on deer hunting optimization algorithm (DHOA) is applied to the Convolutional neural network for the PEMFC parameters identification purpose and it is declared that utilizing the proposed method gives a prediction with higher accuracy for the parameters of the PemFC model.
Abstract: This paper proposes a new optimal method for the parameter identification of a proton exchange membrane fuel cell (PEMFC) for increasing the model accuracy In this research, a new improved version based on deer hunting optimization algorithm (DHOA) is applied to the Convolutional neural network for the PEMFC parameters identification purpose Indeed, the method is implemented to develop the method performance for estimating the PEMFC model parameters The method is then validated based on 4 operational conditions Experimental results declared that utilizing the proposed method gives a prediction with higher accuracy for the parameters of the PEMFC model

15 citations


Journal ArticleDOI
TL;DR: This study presents a multi-objective optimization method to provide an optimal design parameters for the HT-PEMFC based micro-CHP during a 14,000 h lifetime by considering the effect of degradation to optimize the net electrical efficiency and the electrical power generation.
Abstract: Fuel cells due to different useful features such as high efficiency, low pollution, noiselessness, lack of moving parts, variety of fuels used and wide range of capacity of these sources can be the main reasons for their tendency to use them in different applications. In this study, the application of a high temperature proton exchange membrane fuel cell (HT-PEMFC) in a combined heat and power (CHP) plant has been analyzed. This study presents a multi-objective optimization method to provide an optimal design parameters for the HT-PEMFC based micro-CHP during a 14,000 h lifetime by considering the effect of degradation. The purpose is to optimize the net electrical efficiency and the electrical power generation. For the optimization process, different design parameters including auxiliary to process fuel ratio, anodic stoichiometric ratio, steam to carbon ratio, and fuel partialization level have been employed. For optimization, A new technique based on Tent mapping and Levy flight mechanism, called improved collective animal behavior (ICAB) algorithm has been employed to solve the algorithm premature convergence shortcoming. Experimental results of the proposed method has been applied to the data of a practical plant (Sidera30) for analyzing the efficiency of the proposed ICAB based system, it is compared with normal condition and another genetic algorithm based method for this purpose. Final results showed that the difference between the maximum electrical power production under normal condition and ICAB based condition changes from 2.5 kW when it starts and reaches to its maximum value, 3.0 kW, after 14,000 h lifetime. It is also concluded that the cumulative average for the normal and the ICAB based algorithm are 24.01 kW and 27.04 kW, respectively which showed about 3.03 kW cumulative differences.

14 citations


12 Dec 2017
Abstract: Los Modelos de Control Predictivo (MCP) son alternativas prometedoras en la gestion eficiente de la energi­a y los recursos en las edificaciones. Crear un modelo de construccion preciso que sea lo suficientemente simple como para permitir que el problema de MCP resultante sea manejable es una tarea desafiante pero crucial en el desarrollo del control.En este arti­culo muestra el Modelado de Resistencia-Capacitancia para Edificios (MRCE) en Matlab Toolbox que facilita el modelado fi­sico de edificios. Toolbox proporciona un medio para la generacion rapida de modelos de resistencia (capacitancia) lineal a partir de datos basicos de geometri­a de edificios, construccion y sistemas. Ademas, admite la generacion de los correspondientes costos y restricciones potencialmente variables en el tiempo. Toolbox se basa en principios de modelado previamente validados. En un estudio de caso, se genero automaticamente un modelo MRCE a partir de un archivo de datos de entrada EnergyPlus y se compararon sus capacidades predictivas con el modelo EnergyPlus. Los analisis energeticos en regimen estacionario en Matlab son tan precisos como los resultados generados en las herramientas computacionales destinadas exclusivamente a este proposito. La herramienta computacional Matlab se consolida en cada nueva version como una plataforma mas completa y optima para el analisis ingenieri­a y de matematicas aplicadas.

References
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Book
01 Jan 1987
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Abstract: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis und praktische Anwendung der verschiedenen Verfahren zur Identifizierung hat. Da ...

20,022 citations


Book
20 May 2008
Abstract: Although, the basic concept of a fuel cell is quite simple, creating new designs and optimizing their performance takes serious work and a mastery of several technical areas. "PEM Fuel Cell Modeling and Simulation Using Matlab", provides design engineers and researchers with a valuable tool for understanding and overcoming barriers to designing and building the next generation of PEM Fuel Cells. With this book, engineers can test components and verify designs in the development phase, saving both time and money. Easy to read and understand, this book provides design and modelling tips for fuel cell components such as: modelling proton exchange structure, catalyst layers, gas diffusion, fuel distribution structures, fuel cell stacks and fuel cell plant.This book includes design advice and MATLAB and FEMLAB codes for Fuel Cell types such as: polymer electrolyte, direct methanol and solid oxide fuel cells. This book also includes types for one, two and three dimensional modeling and two-phase flow phenomena and microfluidics. This work: features modeling and design validation techniques; covers most types of Fuel Cell including SOFC; includes MATLAB and FEMLAB modelling codes; and, translates basic phenomena into mathematical equations.

231 citations


Proceedings ArticleDOI
10 Jun 2009
TL;DR: In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model around a given operating point, by probing the system in open-loop with variation of input signals.
Abstract: This paper presents the empirical modeling of the gaseous pilot plant which is a kind of interacting series process with presence of nonlinearities. In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model around a given operating point, by probing the system in open-loop with variation of input signals. Three practical approaches are used and their performances are compared to obtain the most suitable approach for modeling of such a system. The models are also tested in the real-time implementation of a linear model predictive control. The selected model is able to well reproduce the main dynamic characteristics of gaseous pilot plant in open loop and produces zero steady-state errors in closed loop control system. Several issues concerning the identification process and the construction of MIMO state space model are discussed.

11 citations


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