[HTML][HTML] Application of machine learning in optimizing proton exchange membrane fuel cells: a review
R Ding, S Zhang, Y Chen, Z Rui, K Hua, Y Wu, X Li… - Energy and AI, 2022 - Elsevier
Proton exchange membrane fuel cells (PEMFCs) as energy conversion devices for
hydrogen energy are crucial for achieving an eco-friendly society, but their cost and …
hydrogen energy are crucial for achieving an eco-friendly society, but their cost and …
A comprehensive and comparative review on parameter estimation methods for modelling proton exchange membrane fuel cell
Abstract Proton Exchange Membrane Fuel Cell (PEMFC) is one of the rising clean form of
energy. Due to various advantages of PEMFCs, they have widespread applications. The …
energy. Due to various advantages of PEMFCs, they have widespread applications. The …
Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer
AA El-Fergany - Renewable Energy, 2018 - Elsevier
In the last years, significant attentions have been paid in the state-of-the-literature to have
precise current/voltage (I/V) polarization curves of polymer exchange membrane fuel cells …
precise current/voltage (I/V) polarization curves of polymer exchange membrane fuel cells …
[HTML][HTML] A new technique for optimal estimation of the circuit-based PEMFCs using developed sunflower optimization algorithm
Z Yuan, W Wang, H Wang, N Razmjooy - Energy Reports, 2020 - Elsevier
This paper proposes a new methodology for the optimal selection of the parameters for
proton exchange membrane fuel cell (PEMFC) models. The proposed method is to optimal …
proton exchange membrane fuel cell (PEMFC) models. The proposed method is to optimal …
A survey of teaching–learning-based optimization
F Zou, D Chen, Q Xu - Neurocomputing, 2019 - Elsevier
Over past few decades, swarm intelligent algorithms based on the intelligent behaviors of
social creatures have been extensively studied and applied for all kinds of optimization …
social creatures have been extensively studied and applied for all kinds of optimization …
Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems
R Rao - Decision science letters, 2016 - growingscience.com
The teaching-learning-based optimization (TLBO) algorithm is finding a large number of
applications in different fields of engineering and science since its introduction in 2011. The …
applications in different fields of engineering and science since its introduction in 2011. The …
A novel approach based on hybrid vortex search algorithm and differential evolution for identifying the optimal parameters of PEM fuel cell
Fuel cells (FCs) penetrated strongly in many applications, modeling of FCs became a major
challenge in recent years due to their characteristics, there are some missing data in the …
challenge in recent years due to their characteristics, there are some missing data in the …
Effective parameters' identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer
M Ali, MA El-Hameed, MA Farahat - Renewable energy, 2017 - Elsevier
The aim of this paper is to develop an accurate model for the polymer electrolyte membrane
fuel cell (PEMFC), that can precisely mimic and simulate the electrical characteristics of …
fuel cell (PEMFC), that can precisely mimic and simulate the electrical characteristics of …
A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling
K Priya, K Sathishkumar, N Rajasekar - Renewable and Sustainable …, 2018 - Elsevier
The widespread use of Proton Exchange Membrane fuel cell for its unique advantages
compelled researchers for precise modelling of its characteristics. Since, modelling …
compelled researchers for precise modelling of its characteristics. Since, modelling …
Benchmark of proton exchange membrane fuel cell parameters extraction with metaheuristic optimization algorithms
Proton exchange membrane fuel cell (PEMFC) models are multivariate with different
nonlinear elements which should be identified accurately to assure dependable modeling …
nonlinear elements which should be identified accurately to assure dependable modeling …