Improvements in identification of fuel cell temperature model

Fagundes, Luis Paulo; Avelar, Henrique José; Fagundes, Frederico Duarte; Cunha, Maria Júlia Rodrigues da; Vincenzi, F. R. S.

doi:10.1109/cobep.2015.7420262

Cited by 4 publications

(5 citation statements)

References 10 publications

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“…In [84], the capabilities of PSO, for global search, and Levenberg-Marquardt algorithm neural network, for fast convergence around the global optimum, are combined to obtain a voltage and thermal model for the PEMFC. In [85,86], nonlinear autoregressive moving average model with exogenous inputs (NARMAX) is employed to obtain a temperature model and a voltage model of PEMFC respectively. In [85], orthogonal least mean square is used to obtain the parameters of NARMAX temperature model first, then the selection is modified by GA.…”

Section: Black Box Based Identificationmentioning

confidence: 99%

“…In [85,86], nonlinear autoregressive moving average model with exogenous inputs (NARMAX) is employed to obtain a temperature model and a voltage model of PEMFC respectively. In [85], orthogonal least mean square is used to obtain the parameters of NARMAX temperature model first, then the selection is modified by GA. In [86], time domain and frequency domain NARMAX model of PEMFC are compared and the time domain is preferred.…”

Section: Black Box Based Identificationmentioning

confidence: 99%

See 1 more Smart Citation

Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes

Kandidayeni

Macías

Amamou

et al. 2018

Journal of Power Sources

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Proton exchange membrane fuel cells (PEMFCs) have become the center of attention for energy conversion in many areas such as automotive industry, where they confront a high dynamic behavior resulting in their characteristics variation. In order to ensure appropriate modeling of PEMFCs, accurate parameters estimation is in demand. However, parameter estimation of PEMFC models is highly challenging due to their multivariate, nonlinear, and complex essence. This paper comprehensively reviews PEMFC models parameters estimation methods with a specific view to online identification algorithms, which are considered as the basis of global energy management strategy design, to estimate the linear and nonlinear parameters of a PEMFC model in real time. In this respect, different PEMFC models with different categories and purposes are discussed first. Subsequently, a thorough investigation of PEMFC parameter estimation methods in the literature is conducted in terms of applicability. Three potential algorithms for online applications, Recursive Least Square (RLS), Kalman filter, and extended Kalman filter (EKF), which has escaped the attention in previous works, have been then utilized to identify the parameters of two well-known semi-empirical models in the literature, Squadrito et. al and Amphlett et. al. Ultimately, the achieved results and future challenges are discussed.

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Section: Black Box Based Identificationmentioning

confidence: 99%

Section: Black Box Based Identificationmentioning

confidence: 99%

Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes

Kandidayeni

Macías

Amamou

et al. 2018

Journal of Power Sources

View full text Add to dashboard Cite

show abstract

“…In [20] a NARMAX model to represent the MIMO relations and to identify the coefficients satisfying the PEMFC voltage simulation is used. Also a NARMAX model is used by [21] to represent PEM and used a GA to the model identification, however, the model only represents the fuel cell temperature.…”

Section: Introductionmentioning

confidence: 99%

Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

Ariza¹,

Correcher²,

Sánchez³

et al. 2018

Preprint

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PEM fuel cell is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and mobile applications. However, the technology demands more research. An important research topic is fault diagnosis and condition monitoring to improve the life and the efficiency and to reduce the operation costs of PEMFC devices. Consequently, there is a need of physical models that let deep analysis. These models must be accurate enough to represent the PEMFC behavior and to allow the identification of different internal signals of a PEM fuel cell. This work presents a PEM fuel cell model that uses the output temperature in a closed loop, so it can represent the thermal and the electrical behavior. The model is used to represent a NEXA Ballard 1.2 kW; therefore it is necessary to fit the coefficients to represent the real behavior. Five optimization algorithms were tested to fit the model, three of them were taken from literature and two were proposed. Finally, the model with the parameters identified was validated with real.

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“…In [20] a NARMAX model to represent the MIMO relations and to identify the coefficients satisfying the PEMFC voltage simulation is used. Also a NARMAX model is used by [21] to represent a PEMFC and used a GA to the model identification, however, the model only represents the fuel cell temperature. Buchlozt and Krebs [22] splits the PEMFC model into a dynamic part and a static part.…”

Section: Introductionmentioning

confidence: 99%

Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

et al. 2018

View full text Add to dashboard Cite

Proton Exchange Membrane Fuel Cell (PEMFC) fuel cells is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and mobile applications. However, the technology demands more research. An important research topic is fault diagnosis and condition monitoring to improve the life and the efficiency and to reduce the operation costs of PEMFC devices. Consequently, there is a need of physical models that allow deep analysis. These models must be accurate enough to represent the PEMFC behavior and to allow the identification of different internal signals of a PEM fuel cell. This work presents a PEM fuel cell model that uses the output temperature in a closed loop, so it can represent the thermal and the electrical behavior. The model is used to represent a Nexa Ballard 1.2 kW fuel cell; therefore, it is necessary to fit the coefficients to represent the real behavior. Five optimization algorithms were tested to fit the model, three of them taken from literature and two proposed in this work. Finally, the model with the identified parameters was validated with real data.

show abstract

Improvements in identification of fuel cell temperature model

Cited by 4 publications

References 10 publications

Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes

Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes

Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

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