Multi-domain and Multi-scale model of a fuel cell electric vehicle to predict the effect of the operating conditions and component sizing on fuel cell degradation

Rašić, Davor; Katrašnik, Tomaž

doi:10.1016/j.enconman.2022.116024

Cited by 13 publications

(3 citation statements)

References 41 publications

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“…Furthermore, the procedure for testing the fuel cell engine using UHP (Ultra High Purity) Hydrogen fuel are as follows: (1) preparing the tools and materials needed for testing and creating test table data; (2) stringing the gas hose from the hydrogen cylinder to the reservoir tube and then to the fuel cell; (3) ensuring that the gas hoses through which the hydrogen gas flows were tightly attached and did not leak by using soap foam; (4) opening the hydrogen regulator valve slowly according to the required pressure; (5) ensuring that all valves to the reservoir were open and the outlet valves to the reservoir were closed; (6) waiting for the required reservoir pressure (1 bar); (7) after the pressure requirement in the reservoir was met, the reservoir output valve slowly was opened; (8) opening the rotameter valve to regulate the hydrogen flow that would enter the fuel cell as needed; (9) the fuel cell would work gradually according to the flow of hydrogen gas; (10) waiting for a while for the fuel cell condition to be ready to be loaded; (11) pressing the load switch on the SCC (Solar Charge Controller); (12) measuring the fuel cell output voltage and current at load 0 using a digital voltampere meter; (13) varying the load (in the form of 10 W and 16 W DC lamps) from 10 W load to the highest load of 60 W; (14) recording the fuel cell voltage and current parameters for each new load addition in the test table; (15) repeating test steps number 8 to number 14 with different variations of hydrogen discharge; (16) after completing taking data on the fuel cell engine, the load was gradually reduced until it reached the zero load position; (17) closing the hydrogen cylinder regulator valve; (18) waiting for the remaining hydrogen in the reservoir to flow into the fuel cell until it run out; (19) closing all valves and valves leading to the fuel cell; (20) cleaning the test equipment and placing it in a safe condition.…”

Section: Methodsmentioning

confidence: 99%

“…One of the efforts as an energy source solution for the future is the fuel cell. The fuel cell is an electrochemical device that converts chemical energy as fuel into electrical energy directly, which is quite promising as a generator with high efficiency and low environmental impact [5]- [8]. The fuel cell is also an electrochemical technology fueled by hydrogen, continuously converting chemical energy into electrical energy as long as there are fuel and oxidizing agents.…”

Section: Introductionmentioning

confidence: 99%

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Application of a PEM Fuel Cell Engine as a Small-Scale Power Generator for Small Cars with Different Fuel Concentrations

Herlambang,

Sulistiyo,

Margana

et al. 2023

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A fuel cell power generation system is a renewable energy system that works based on electrochemical processes and produces a direct electric current (DC). Specifically, a Proton Exchange Membrane (PEM) Fuel Cell can operate at low temperatures and produce an efficiency of around 40-60%. In this study, the performance test of the PEM Fuel Cell for power generation was carried out by supplying hydrogen gas using hydrogen from the electrolysis of the hydrogen generator with a variation of KOH catalyst solution with a concentration of 0.5 M; 1.0 M; 1.5 M; 2 M and using Ultra High Purity (UHP) hydrogen with various flow rates of 250 mL/min, 300 mL/min, 350 mL/min, 400 mL/min, 450 mL/min, and 500 mL/min. The test results showed that the output power of hydrogen produced by the electrolysis process was 10.8 W at a concentration of 1 M solutions at an input current of 20 A. The greater the concentration of the catalyst solution, the smaller the electrical power required for the electrolysis process. However, the hydrogen power supply produced by the hydrogen generator was not optimal, so it did not meet the needs of the PEM Fuel Cell. As a result, the PEM Fuel Cell could not work. Meanwhile, testing with UHP hydrogen produced the highest electrical power of 31.588 W at a flow rate of 450 mL/min with a load of 20 W. It indicates that the PEM Fuel Cell is optimal at the output power value with an efficiency of 69.80%.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of a PEM Fuel Cell Engine as a Small-Scale Power Generator for Small Cars with Different Fuel Concentrations

Herlambang,

Sulistiyo,

Margana

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Several factors can affect how well fuel cells function. Some of them are the operational circumstances [7], flow channel design [8], fuel cell component size [9], material qualities, and operating conditions. The flow channel's design is crucial since it greatly affects how efficiently fuel cells function [10].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Geometric Properties of Fuel Cell Components

YAVUZ¹,

KAHRAMAN

2023

International Journal of Automotive Science and Technology

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Due to factors including low emission values, great energy efficiency, and reduced environmental contamination, fuel cells have gained popularity recently. Fuel cells using polymer electrolyte membranes can distribute reactant gases through gas flow channels and remove water that forms during the reaction from the fuel cell. This study looked at how different channel sizes and channel cross-section geometries (rectangular, triangular, and semicircular) affected the distribution of current density, oxygen concentration, velocity, and temperature parameters on the cathode catalyst in the flow channels of a single-channel PEM fuel cell at 0.75 V cell voltage. The model with the highest current density and consequently the best fuel cell performance was determined to be 9 x 10-5 A/cm2 in a channel with a height and breadth of 0.1 cm and A = 1 cm2, according to the data obtained. The flow channel length was assessed at 0.2 in the analysis results for all models because it did not alter with the oxygen concentration distribution. In varied channel designs with the same area, it has been found that the velocity distribution varies inversely with the current density. The maximum velocity value recorded at this location was 33.1 m/s in a semicircular canal with a R of 0.34 mm. It has been discovered that fuel cells from more places operate better as a result.

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Multi‐step performance degradation prediction method for proton‐exchange membrane fuel cell stack using1Dconvolution layer andCatBoost

Zhang,

Dong,

et al. 2024

Adaptive Control & Signal

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SummaryThe increasing environmental issues such as climate change and air pollution require energy saving and emission reduction in various fields, such as manufacturing, building, and transportation. To address the above problem, proton‐exchange membrane fuel cells (PEMFC) gradually become promising green energy conversion device due to the advantages of zero pollution, high efficiency, and low operating noise. However, the durability problem has extremely limited the PEMFC large‐scale commercial application. To prolong the service life of PEMFC, performance degradation prediction is an effective method. This paper proposes a multi‐step performance degradation prediction method for proton‐exchange membrane fuel cells based on CatBoost feature selection, convolution computing, and interactive learning mechanism. CatBoost is used to evaluate the importance of the monitor parameters on performance degradation. The evaluation results and PEMFC degradation mechanism analyses are used to select the monitor parameters for construing the prediction model. Based on the 1D convolutional layer and the interactive learning mechanism, the prediction model is proposed to extract the deep features from the monitor data to predict the performance degradation of the fuel cell system. In particular, the multi‐step prediction is performed by the configurable sliding window. The effectiveness of the proposed method is verified on real experiment datasets, and the experiment results show that the proposed method is particularly effective for multi‐step degradation prediction and decreases the computation by feature selection and 1D convolution layer.

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Multi-domain and Multi-scale model of a fuel cell electric vehicle to predict the effect of the operating conditions and component sizing on fuel cell degradation

Cited by 13 publications

References 41 publications

Application of a PEM Fuel Cell Engine as a Small-Scale Power Generator for Small Cars with Different Fuel Concentrations

Application of a PEM Fuel Cell Engine as a Small-Scale Power Generator for Small Cars with Different Fuel Concentrations

Performance Analysis of Geometric Properties of Fuel Cell Components

Multi‐step performance degradation prediction method for proton‐exchange membrane fuel cell stack using1Dconvolution layer andCatBoost

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