Performance Prediction of Proton Exchange Membrane Fuel Cells (PEMFC) Using Adaptive Neuro Inference System (ANFIS)

Wilberforce, Tabbi; Olabi, Abdul Ghani

doi:10.3390/su12124952

Cited by 33 publications

(22 citation statements)

References 36 publications

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“…This is ascertained by non-uniform current distribution when the RH is varied from 95% to 70%. 22 Related work by Wilberforce et al 23 shows similar effects exhibited by back pressure and air stoichiometry.…”

Section: Effect Of Relative Humiditymentioning

confidence: 70%

“…In 2016, Zhang et al 23 identified certain key parameters that are important for the development of fuel cell with homogeneity, overall stability, performance and resistance losses. They reported that water management and reactant gas concentration are the vital parameters for an efficient fuel cell.…”

Section: Design Parameters and Their Effectsmentioning

confidence: 99%

“…It was revealed that the optimal configuration of several parameters, such as higher back pressure to enhance performance while maintaining uniformity and current distribution, increased RH to enhance homogeneity, increased air stoichiometry for local stability which are necessary to design detailed models and simulations. Other vital parameters include water management and gas concentration 23 …”

Section: Design Parameters and Their Effectsmentioning

confidence: 99%

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Review of operating condition, design parameters and material properties for proton exchange membrane fuel cells

et al. 2020

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Summary Studies into the effects of parameters used in the design of proton exchange membrane (PEM) fuel cell have been done. All the modelling parameters considered influenced the performance of the PEM fuel cells. The effect of the operating condition is shown to be significant. Increasing the operating temperature and operating pressure increases the mobility of ions and as a result the ionic conductivity is increased. In addition, the membrane is dried out when the correct humidity is not provided which increases membrane degradation. Adopting good design parameter is necessary for the efficient transportation of both reactants (fuel and oxygen). With regards to the use of flow plates, the serpentine flow plate is highly recommended. Material properties are very important in material selection and new product development. For the membrane electrode area (MEA); the membrane, the ionic conductivity is very important and should be given an important consideration. This investigation thoroughly examined operating condition, design parameters and material properties necessary for PEM fuel cells experiment. The investigation will further accelerate the commercialization of fuel cells and its integration in the automotive industry.

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Section: Effect Of Relative Humiditymentioning

confidence: 70%

Section: Design Parameters and Their Effectsmentioning

confidence: 99%

Section: Design Parameters and Their Effectsmentioning

confidence: 99%

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Review of operating condition, design parameters and material properties for proton exchange membrane fuel cells

et al. 2020

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“…Fig. 2, shows the typical polarization curve of proton exchange membrane FC (Wilberforce and Olabi, 2020). Turbochargers belong to the aerodynamic compressors, while other compressors (or mechanical paddles) belong to the volumetric compressors (Robison and Beaty, 1992), the important criteria for choosing a compression system suitable for the FCV application listed and compared in the form of weighting and rating matrix.…”

Section: Fig 1 Fc System Flow Diagrammentioning

confidence: 99%

Fuel Cell designing with optimal high speed air compressor

Ahsan

Mehmood

Zaidi³

2021

ETE

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This paper discusses different air management technologies for fuel cell systems. Two different types of compressors are analyzed for Proton-exchange membrane fuel cells (PEMFC). Some important criteria are analyzed thoroughly for the selection of turbo compressor among different types of compressors illustrated with the help of matrix representations. The impacts of various input parameters for Fuel Cell (FC) are also explained thoroughly. Later the numerical modeling of an automobile fuel cell system using a high speed turbo-compressor for air supply is explained. The numerical model incorporates the important input parameters related with air and hydrogen. It also performed energy and mass balances across different components such as pump, fan, heat-exchanger, air compressor and also keeps in consideration the pressure drop across the flow pipes and various mechanical parts. The model is solved to obtain the characteristics of the FC system at different operating conditions. Therefore, it can be concluded that the high speed turbo compressor with a turbo-expander can have significant effects on the overall system power and efficiency.

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“…To better understand the functionality of this system, Figure 3 gives an example of two inputs and one output. 31 Experimental study…”

Section: Layermentioning

confidence: 99%

Hybridization of time synchronous averaging, singular value decomposition, and adaptive neuro fuzzy inference system for multi-fault bearing diagnosis

Touzout

Benazzouz

Gougam

et al. 2020

Advances in Mechanical Engineering

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Bearing diagnosis has attracted considerable research interest; thus, researchers have developed several signal processing techniques using vibration analysis to monitor the rotating machinery’s conditions. In practical engineering, features extraction with most relevant information from experimental vibration signals under variable operation conditions is still regarded as the most critical concern. Therefore, actual works focus on combining Time Domain Features (TDFs) with decomposition techniques to obtain accurate results for defect detection, identification, and classification. In this paper, a new hybrid method is proposed, which is based on Time Synchronous Averaging (TSA), TDFs, and Singular Value Decomposition (SVD) for the feature extraction, then the Adaptive Neuro-Fuzzy Inference System (ANFIS) which gathers the advantages of both neural networks and fuzzy logic is applied for the classification process. First, TSA is used to reduce noises in the vibration signal by extracting the periodic waveforms from the disturbed data; thereafter, TDFs are applied on each synchronous signal to construct a feature matrix; afterwards, SVD is performed on the obtained matrices to remove the instability of statistical values and select the most stable vectors. Finally, ANFIS is implemented to provide a powerful automatic tool for features classification.

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Performance Prediction of Proton Exchange Membrane Fuel Cells (PEMFC) Using Adaptive Neuro Inference System (ANFIS)

Cited by 33 publications

References 36 publications

Review of operating condition, design parameters and material properties for proton exchange membrane fuel cells

Review of operating condition, design parameters and material properties for proton exchange membrane fuel cells

Fuel Cell designing with optimal high speed air compressor

Hybridization of time synchronous averaging, singular value decomposition, and adaptive neuro fuzzy inference system for multi-fault bearing diagnosis

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