Environmental and economic analyses of fuel cell and battery-based hybrid systems utilized as auxiliary power units on a chemical tanker vessel

Korkmaz, S. Aykut; Erginer, Kadir Emrah; Yüksel, Onur; Konur, Olgun; Çolpan, C. Özgür

doi:10.1016/j.ijhydene.2023.01.320

Cited by 14 publications

(8 citation statements)

References 26 publications

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“…Their growing prominence in sectors such as transportation [16], distributed generation, and microgrids underlines the importance of this research, which explores the field of these clean energy options and future advancements in fuel cell technology [17]. The construction of accurate models for PEMFCs has become a pivotal point for researchers [18] who seek to establish reliable models using software programs that closely correlate with experimental results [19]. The significance of PEMFC modeling lies in its impact on analyses, particularly in microgrids and smart grid applications [20].…”

Section: A Problem Under Studymentioning

confidence: 99%

Parameters Estimation of Proton Exchange Membrane Fuel Cell Model Based on an Improved Walrus Optimization Algorithm

Alqahtani,

Hasanien,

Alharbi

et al. 2024

IEEE Access

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Proton Exchange Membrane Fuel Cells (PEMFCs) play a crucial role in the advancement of clean hydrogen vehicles. Their ability to convert hydrogen into electricity makes them promising candidates to replace conventional engines. However, optimizing their performance and efficiency necessitates accurate modeling techniques capable of simulating their behavior. In this context, this paper proposes an advanced approach for precise parameter estimation in PEMFC models. Employing an Enhanced Walrus Optimization (EWO) algorithm integrated with Lévy flight exploration, the approach tackles the inherent nonlinearity of PEMFC systems. The technique aims to minimize the squared error between measured and simulated terminal voltage, thereby ensuring superior accuracy and robustness compared to established algorithms. The effectiveness of the proposed model is validated through comparisons between theoretical simulations and experimental measurements. The findings demonstrate the efficacy of the EWO algorithm, consistently outperforming previously published algorithms and achieving notably lower errors. Moreover, the incorporation of Lévy flights enhances the algorithm's capabilities, leading to expedited convergence and more accurate parameter estimations. Beyond facilitating precise parameter estimation, this enhanced modeling strategy opens avenues for refining design and optimization strategies in fuel cell research and development. The major contributions of this paper include the enhancement of the WO algorithm, evaluation of theoretical model accuracy, and robustness assessment of the EWO in optimizing the PEMFC model. By furnishing accurate models validated through experimental evidence, this enhanced modeling strategy paves the way for refining design and optimization strategies in fuel cell research and development.

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Section: A Problem Under Studymentioning

confidence: 99%

Parameters Estimation of Proton Exchange Membrane Fuel Cell Model Based on an Improved Walrus Optimization Algorithm

Alqahtani,

Hasanien,

Alharbi

et al. 2024

IEEE Access

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“…It can be calculated using a modified version of the Nernst Equation (3). To consider the variations in pressure and temperature compared to the typical conditions of 298.15 K and 1 bar [19], we use the following:…”

Section: Mathematical Model Of Pem Fuel Cellmentioning

confidence: 99%

“…Furthermore, Mh can be classified into four primary categories: swarm-based, nature-based, physics-based, and evolutionary-based. These categories have been thoroughly examined by researchers in the literature to identify the most effective values for the unidentified parameters of PEMFC models [19]. From the categories mentioned above, the genetic algorithm (GA) was utilized to address the optimization challenge of modeling PEMFCs [20].…”

Section: Introductionmentioning

confidence: 99%

Extracting Accurate Parameters from a Proton Exchange Membrane Fuel Cell Model Using the Differential Evolution Ameliorated Meta-Heuristics Algorithm

Kanouni,

Laib

2024

Energies

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The electrochemical proton exchange membrane fuel cell (PEMFC) is an electrical generator that utilizes a chemical reaction mechanism to produce electricity, serving as a sustainable and environmentally friendly energy source. To thoroughly analyze and develop the features and performance of a PEMFC, it is essential to use a precise model that incorporates exact parameters to effectively suit the polarization curve. In addition, parameter extraction plays a crucial role in the simulation analysis, evaluation, optimum control, and fault detection of the proton exchange membrane fuel cell (PEMFC) system. Despite the development of many algorithms for parameter extraction in PEMFC, obtaining accurate and trustworthy results rapidly remains a challenge. This study presents a hybridized algorithm, namely differential evolution ameliorated (DEA) for reliably estimating PEMFC model parameters. To evaluate the proposed DEA-based parameter identification, a comparison analysis with previously published methods is conducted using MATLAB/SimulinkTM (R2016b, MathWorks, Natick, MA, USA) in terms of system correctness and convergence process. The proposed DEA algorithm is tested to extract the parameters of two PEMFC models: SR-12,500 W and 250 W. The sum of the squared errors (SSE) between the experimental and the obtained voltage data is defined as an objective function. The simulation results prove that the suggested DEA algorithm is capable of identifying the optimal PEMFC parameters rapidly and accurately in comparison with other optimization algorithms.

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“…The electric work, denoted by the symbol ΔG and the electric charge Q (in coulombs) divided by the electric potential E (in volts), can be found by solving equations ( 6) through (7).…”

Section: Pemfcs Systemmentioning

confidence: 99%

“…Nevertheless, the advantages of the PEMFCs make them perfect alternatives to fossil based power systems. Technical specifications related to different research topics of PEMFCs can be tracked in several publications [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

AI based Metaheuristic Optimization of PEMFC Control System for Robust and Efficient Operation

Aboshosha

Gouda

Awad

et al. 2023

Preprint

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Proton Exchange Membrane Fuel Cells (PEMFC) have several merits over the other fuel cells like low operating temperature, high power density, light weight, and robustness, fitting them in a wide variety of green energy applications. The most important application area of the PEMFC is hydrogen cars (Fuel Cell Electric Vehicles – FCEV), stationary and portable hydrogen power systems. Throughout the presented research work the complete three cycles of the fuel cell control are presented which are the control system, the FCEV control and the AI based metaheuristic optimization. The presented algorithm includes the PI controller – PI-based HHO-PI-based AEO-PI-based GWO-PI-based PSO. An objective statistical comparison among the presented algorithms to select the best one of them according to perfect criteria.

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Environmental and economic analyses of fuel cell and battery-based hybrid systems utilized as auxiliary power units on a chemical tanker vessel

Cited by 14 publications

References 26 publications

Parameters Estimation of Proton Exchange Membrane Fuel Cell Model Based on an Improved Walrus Optimization Algorithm

Parameters Estimation of Proton Exchange Membrane Fuel Cell Model Based on an Improved Walrus Optimization Algorithm

Extracting Accurate Parameters from a Proton Exchange Membrane Fuel Cell Model Using the Differential Evolution Ameliorated Meta-Heuristics Algorithm

AI based Metaheuristic Optimization of PEMFC Control System for Robust and Efficient Operation

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