Electronic modeling of a PEMFC with logarithmic amplifiers

Alberro, Mikel; Marzo, F.F.; Manso, Ángel Pérez; Domínguez, Víctoriano; Barranco, J.; Garikano, Xabier

doi:10.1016/j.ijhydene.2015.01.070

Cited by 15 publications

(5 citation statements)

References 21 publications

(6 reference statements)

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“…where I is the individual cell current (A), t is the time in seconds (s) that it takes for oxygen to flows over the electrode, N A is Avogadro's constant (6.022 × 10 23 mol −1 ) [25], and e is electron charge (1.6 × 10 −19 C) [26].…”

Section: Cathode Flow Modelmentioning

confidence: 99%

Investigating the Parameter-Driven Cathode Gas Diffusion of PEMFCs with a Piecewise Linearization Model

Wang

You

et al. 2023

Energies

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Improving mass transfer in gas diffusion layers is critical to achieving high-performance proton-exchange membrane fuel cells (PEMFCs). Leaks through the interface between the gas and the membrane electrode assembly frame have been widely investigated, and the controllability of the cathode gas diffusion has not been achieved in most studies. In this study, we develop a structural parameter to investigate the controllability of the gas diffusion mechanism in the cathode in order to improve upon the design and performance of PEMFCs. This parameter accounts for the cathode gas diffusion layer porosity and carbon loading inside the catalyst layer. It is comprehensively calculated to relax the two segments’ distribution along three directions of the coordinate axis. The experimental and simulation results show that the obtained values of the parameter vary and change during voltage stabilization. According to the results, regardless of the materials in the cathode gas diffusion layer, the same steady-state voltage is obtained when the parameter is fixed. The cell could be controllably operated for a wide range of diffusion layer thicknesses by selecting the optimal parameter.

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Section: Cathode Flow Modelmentioning

confidence: 99%

Investigating the Parameter-Driven Cathode Gas Diffusion of PEMFCs with a Piecewise Linearization Model

Wang

You

et al. 2023

Energies

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“…Here, three irreversibilities including ohmic, activation, and concentration losses have been considered which are formulated below, respectively:

V_{O} = t_{membrane} \times i \times {[(0.005 \times λ_{membrane} - 0.0033) \exp (4.18 - T_{FC}^{- 1})]}^{- 1}

V_{a} = ((), \frac{α_{normalA} + α_{normalC}}{α_{normalA} \times α_{normalC}}) \times \frac{{RT}_{FC}}{F \times r_{f}} \times \ln ((), \frac{i}{i_{0}})

V_{C} = i \times {(β_{1} \times \frac{i}{i_{\max}})}^{β_{2}}

where λ membrane is the mean value for the membrane water content is the average of the water content on the anode/membrane interface ( λ a ) and the cathode/membrane interface ( λ c ), and i 0 represents exchange current density and is formulated as follows:

i_{0} ((), T) = 108 \times 10^{- 23} \times \exp ((), 0.086 \times T_{FC})

…”

Section: Modeling Of the Systemmentioning

confidence: 99%

“…Here, three irreversibilities including ohmic, activation, and concentration losses have been considered which are formulated below, respectively 44 :…”

Section: Modeling Of the Systemmentioning

confidence: 99%

Application of the meta‐heuristics for optimizing exergy of a HT‐PEMFC

Han

Khodaei

2020

Int J Energy Res

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Summary The aim of this study is to analyze the exergy efficiency of a high‐temperature proton exchange membrane fuel cell. To do this purpose, meta‐heuristic technique has been used. First, the model of a membrane fuel cell is simulated and the polarization diagram shows a potent agreement with empirical data. Then, a new improved version of collective animal behavior algorithm is utilized for evaluating and optimizing the thermodynamic irreversibility, exergy efficiency, and work of the fuel cell. The algorithm uses opposition‐based learning and Lévy flight for improving the algorithm's premature convergence shortcoming. The result of this study shows that by comparison with standard collective animal behavior algorithm, genetic algorithm, and empirical results, the proposed algorithm has better achievements for both terms of optimal value finding and convergence strength.

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“…This model only exhibits the characteristics of ROP. The fuel cell electrical model was emulated using logarithmic amplifiers 19 . This model exhibits the characteristics of region of activation and ohmic polarization.…”

Section: Introductionmentioning

confidence: 99%

“…The fuel cell electrical model was emulated using logarithmic amplifiers. 19 This model exhibits the characteristics of region of activation and ohmic polarization. The summary of literature review proton-exchange membrane fuel cell emulator is shown in Table 1.…”

mentioning

confidence: 99%

PSO optimized PI controlled DC‐DC buck converter‐based proton‐exchange membrane fuel cell emulator for testing of MPPT algorithm and battery charger controller

Premkumar¹,

Vishnupriya

Thamizhselvan³

et al. 2020

Int Trans Electr Energ Syst

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Summary In this article, particle swarm optimized proportional integral (PI) controlled DC‐DC buck converter‐based proton‐exchange membrane fuel cell emulator has been proposed to test the maximum power point tracking algorithm and battery charging controller. Particle swarm optimization is used to optimize the proportional gain (Kp) and integral gain (Ki) of the proportional integral controller for emulating the characteristics of the PEM fuel cell. The simulation model of the proposed PEM fuel cell emulator is created and tested using MATLAB Simulink package. To validate the effectiveness of the proposed PEM fuel cell emulator, it is tested under different operating conditions. The polarization characteristics of the PEM fuel cell emulator are compared with PEM fuel cell reference model. The suitability of the PEM fuel cell emulator has been tested with MPPT algorithm and MPPT battery charging controller. Also, real‐time testing of the proposed PEM fuel cell emulator has been realized through experimental set up and the corresponding results are analyzed.

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Electronic modeling of a PEMFC with logarithmic amplifiers

Cited by 15 publications

References 21 publications

Investigating the Parameter-Driven Cathode Gas Diffusion of PEMFCs with a Piecewise Linearization Model

Investigating the Parameter-Driven Cathode Gas Diffusion of PEMFCs with a Piecewise Linearization Model

Application of the meta‐heuristics for optimizing exergy of a HT‐PEMFC

PSO optimized PI controlled DC‐DC buck converter‐based proton‐exchange membrane fuel cell emulator for testing of MPPT algorithm and battery charger controller

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