Control-oriented thermal management of solid oxide fuel cells based on a modified Takagi–Sugeno fuzzy model

Yang, Jie; Li, Xi; Mou, Hong-Gang; Li, Jian

doi:10.1016/j.jpowsour.2008.12.012

Cited by 41 publications

(15 citation statements)

References 24 publications

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“…Full descriptions of these expressions can be found in published works [50,35,[51][52][53][54]. The methodology used here has been previously used by others, including [18,32,33,36,[40][41][42][55][56][57][58], who have compared predictions to both cell and system level experimental data [18,33,40,41,59,60]. The model used here is based on conservation of mass, species, and energy, as well as equations of convective and conductive heat transfer, steam reformation reactions, momentum, and fuel cell electrochemistry.…”

Section: Fuel Cell Stackmentioning

confidence: 99%

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Investigation of thermal control for different SOFC flow geometries

2016

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h i g h l i g h t s Thermal control of cross flow SOFC is investigated. Changing flow directions in a subset of channels can improve thermal profiles. Non uniform air flow improves thermal profile at the expense of small efficiency loss. Advanced controllers minimize thermal variations for large changes in power demand. a b s t r a c t A dynamic solid oxide fuel cell (SOFC) model is used to investigate the effects of different flow arrangements, as well as those of non-uniform air flow across channels, on temperature profile and thermal gradients under transient and steady state response. A high performance multi-input multi-output feedback controller has been developed to minimize SOFC spatial temperature variations during changes in power demands for different flow patterns. Numerical results show that the controller would result in negligible temperature variations for the modified cross-flow arrangement proposed here, even for large changes in the power drawn. The combination of a high performance controller and design modification results in a more uniform temperature profile at steady state nominal conditions, and modest variations in temperature profile, from the nominal, for ±15% change in power. Similarly, non-uniform air flow rate decreases the temperature gradient as well as maximum temperature across the cell, though its effect is less pronounced in the closed loop response.

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Section: Fuel Cell Stackmentioning

confidence: 99%

“…Typically, increased bulk air flow can be used to reduce temperature gradients and thermal stress [16,23,[30][31][32][33], but additional air flow comes with costs. The primary cost is the power requirement of a blower needed to push the additional air through the system.…”

Section: Introductionmentioning

confidence: 99%

Investigation of thermal control for different SOFC flow geometries

2016

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“…SOFC models, which concentrate on effects of temperature dynamics, were previously investigated in the literature (Sedghisigarchi & Feliachi, 2004;Goel et al, 2006;Wang & Nehrir, 2007a;Wu et al, 2008a;Ren et al, 2010;Gebregergis & Pillay, 2010;Yang et al, 2009). The output power of fuel cell is closely related to the temperature of the fuel cell unit (Sedghisigarchi & Feliachi, 2004).…”

Section: Dynamic Model Of Thermal Based Sofc Systemmentioning

confidence: 99%

The performance of thermal based modified solid oxide fuel cell (SOFC) model under different DC load conditions

Gelen

Yalçınöz

2015

J Engin Res

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“…However, the solution to these differential equations is very difficult and time-consuming (Wang et al, 2008). By far, several identification models of the SOFC have been reported for predicting performance and control-oriented applications (Jurado, 2004;Huo et al, 2008;Yang et al, 2009;Zhang and Feng, 2009;Wu et al, 2011), which avoids using complicated differential equations to describe the stack. The SOFC dynamic identification models developed by Yang et al (2009) and Wu et al (2011) include temperature and heat transfer dynamics but no electrochemical dynamics.…”

Section: Introductionmentioning

confidence: 99%

“…By far, several identification models of the SOFC have been reported for predicting performance and control-oriented applications (Jurado, 2004;Huo et al, 2008;Yang et al, 2009;Zhang and Feng, 2009;Wu et al, 2011), which avoids using complicated differential equations to describe the stack. The SOFC dynamic identification models developed by Yang et al (2009) and Wu et al (2011) include temperature and heat transfer dynamics but no electrochemical dynamics. Jurado (2004), Huo et al (2008), and Zhang and Feng (2009) considered the electrochemical characteristics in their identification models.…”

Section: Introductionmentioning

confidence: 99%

Control-oriented dynamic identification modeling of a planar SOFC stack based on genetic algorithm-least squares support vector regression

Huo

Zhu

et al. 2014

J. Zhejiang Univ. Sci. A

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For predicting the voltage and temperature dynamics synchronously and designing a controller, a control-oriented dynamic modeling study of the solid oxide fuel cell (SOFC) derived from physical conservation laws is reported, which considers both the electrochemical and thermal aspects of the SOFC. Here, the least squares support vector regression (LSSVR) is employed to model the nonlinear dynamic characteristics of the SOFC. In addition, a genetic algorithm (GA), through comparing a simulated annealing algorithm (SAA) with a 5-fold cross-validation (5FCV) method, is preferably chosen to optimize the LSSVR's parameters. The validity of the proposed LSSVR with GA (GA-LSSVR) model is verified by comparing the results with those obtained from the physical model. Simulation studies further indicate that the GA-LSSVR model has a higher modeling accuracy than the LSSVR with SAA (SAA-LSSVR) and the LSSVR with 5FCV (5FCV-LSSVR) models in predicting the voltage and temperature transient behaviors of the SOFC. Furthermore, the convergence speed of the GA-LSSVR model is relatively fast. The availability of this GA-LSSVR identification model can aid in evaluating the dynamic performance of the SOFC under different conditions and can be used for designing valid multivariable control schemes.

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Control-oriented thermal management of solid oxide fuel cells based on a modified Takagi–Sugeno fuzzy model

Cited by 41 publications

References 24 publications

Investigation of thermal control for different SOFC flow geometries

Investigation of thermal control for different SOFC flow geometries

The performance of thermal based modified solid oxide fuel cell (SOFC) model under different DC load conditions

Control-oriented dynamic identification modeling of a planar SOFC stack based on genetic algorithm-least squares support vector regression

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