An Electronic Measurement Instrumentation of the Impedance of a Loaded Fuel Cell or Battery

Rouane, Amar; Elmoznine, R.

doi:10.3390/s7102363

Cited by 10 publications

(5 citation statements)

References 8 publications

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“…Moreover, these values are almost identical to that obtained by Selmene et al using the least square method [23]. These results are also close to the mesurad values found by Reddad [24] et al and Rouane [25] who worked on a fuel cell having the same characteristics as the Nexa fuel cell.…”

Section: Simulations and Validationsupporting

confidence: 90%

Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm

Yahia

Allagui

Bouaicha

et al. 2017

IJECE

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<p>The objective of this paper is the PEM fuel cell impedance model parameters<strong> </strong>identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 W PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.</p>

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Section: Simulations and Validationsupporting

confidence: 90%

Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm

Yahia

Allagui

Bouaicha

et al. 2017

IJECE

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“…Despite these difficulties, some recent papers propose and test sensor technologies for measuring the internal parameters of FCs during their operation. In particular, the measurement of the temperature and temperature gradient in SOFCs [ 35 , 36 , 37 ] has been proposed by adopting thin thermocouples, the measurement of temperature and humidity in PEMFCs [ 38 , 39 ] using multi-functional micro sensors, and the measurement of the losses due to the impedance increase inside the SOFC electrodes [ 40 , 41 , 42 , 43 ] using the electrochemical impedance spectroscopy. Therefore, in the final part of this study, we assume that the temperature gradient and the impendence losses can be measured inside SOFCs and introduce the maximum temperature gradient and the activation losses of the cathode as two additional monitored variables to assess the potential improvement in the performance of fault diagnosis system.…”

Section: Measurements and Faults In The Sofc Plant And Related Modmentioning

confidence: 99%

Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

Costamagna

Giorgi

Gotelli

et al. 2016

Sensors

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The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements.

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“…Fig. 5 represents the Nyquist graph of the impedance of the Nexa fuel cell obtained in the experiments [16][17][18]. Measurements were made in a current range from 1 A to 10 A and a frequency band of 8 MHz to 12.4 kHz.…”

Section: Electrical Model-cell 1 To 45mentioning

confidence: 99%

Polymer Electrolyte Fuel Cell Stack Modelling in VHDL-AMS Language with Temporal and EIS Experimental Validations

Rouane¹,

Chrenko²,

Kourtiche³

et al. 2014

JEPE

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This paper deals with two basic issues of fuel cell research: modelling and experimental validation. In particular, the EIS (electrochemical impedance spectroscopy) technique is applied to a PEMFC (proton exchange membrane fuel cell). Experiments have been performed using a low-cost test bench and instrumentation developed around a 1,200 W Ballard Nexa fuel cell system. An electrical and dynamic model in VHDL-AMS language for PEM fuel cell stack is described. The privileged approach in this paper is an electrical method. Few papers deal with the modelling of a fuel cell in VHDL-AMS language with an electric approach. The fuel cell is characterised cell wise in VHDL-AMS; AC and DC measurements show the good agreement between the simulation results of the model and those measured in experiments. The model is capable to predict accurate stack profiles. The model is validated using temporal and impedance spectroscopy method; the impedance spectroscopy is performed at low and high frequencies.The experimental and simulated Nyquist plots show that the frequency response of the fuel cell stack can be predicted by the proposed fuel cell stack model. At high frequencies, comparisons between experimental and model impedance results are performed and show some similarities between the two Nyquist. Error between the two approaches is below 1.5%.

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An Electronic Measurement Instrumentation of the Impedance of a Loaded Fuel Cell or Battery

Cited by 10 publications

References 8 publications

Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm

Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm

Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

Polymer Electrolyte Fuel Cell Stack Modelling in VHDL-AMS Language with Temporal and EIS Experimental Validations

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