Optimal parameter estimation of PEM fuel cell using slime mould algorithm

Abstract

For the modeling and analysis of hydrogen fuel cells, reliable kinetic models are of utmost important. Proton exchange membrane fuel cell (PEMFC) is a complicated, multivariable device. Mathematical simulation of the PEMFC typically results in nonlinear parameter estimation issues, often involving more than one local minima. This paper proposes to solve the PEMFC model estimation issues with a slime mould (SM)-based optimization algorithm.Findings on several benchmark test functions show that, the SMA outperforms the other rest of the compared algorithms. Furthermore, an experimental finding indicates that the predictive outcomes of the model are in better alignment with the real experimental results. The SMA therefore is a valuable and effective method for estimating the parameters of PEMFC models and can be used for other specific fuel cell issues. After estimating the parameter of fuel cell, nonparametric test is obtained and from this test it is justified that the SMA is better than the rest of the compared algorithms.

Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review

“…al. ( 2021c ) 2021 0 25 Chimp Optimization Algorithm Mathematical and Engineering Optimization problems (Khishe and Mosavi 2020a ; Kaur et al 2021 ; Dhiman 2021 ) Digital Filters (Kaur et al 2021 ), Neural Network (Khishe and Mosavi 2020a ), Hu et al 2021 ), MLT based Image Segmentation (Houssein et al 2021d ), Feature Selection (Wu et al 2021b , Piri et al 2021 ), Image Classification (Annalakshmi and Murugan 2021 ), Electrical Distribution Network (Fathy et al 2021 ), Power System Stabilizer (Aribowo et al 2021b ), Solar Photovoltaic Systems (Nagadurga et al 2021 ), Solar Dish Sterling Power plant (Zayed et al 2021a ), Tunnel FET architecture (Bhattacharya et al 2021 Khishe and Mosavi ( 2020a ) 2020 87 26 Slime Mould Algorithm Mathematical and Engineering Optimization problems (Li et al 2020b ), Yin et al 2022 ), Artificial Neural Network (Zubaidi et al 2020 ), Solar Photovoltaic Systems (Kumar et al 2020 ) (Mostafa et al 2020 Yousri et al 2021 ;El-Fergany 2021a ), Power System Stabilizer (Ekinci et al 2020 ), Servo Systems (Precup et al 2021 ), MLT based Image Segmentation (Liu et al 2021a ; Naik et al 2020 ; Lin et al 2021 ; Zhao et al 2021b ), Image Classification (Wazery et al 2021 ), Feature Selection (Abdel-Basset et al 2021b ), Numerical Optimization (Sun et al 2021b ), Urban Water Resources (Yu et al 2021 ), PEM Fuel Cell Parameter Identification (Gupta et al …”

Multiscale Modelling of Fuel Cells and Related Energy Conversion Systems

“…To size and rate FCs, reliable kinetic models are needed, but they are multivariable device. Simulation involves nonlinear parameter estimation issues, often involving more than one local minima imposing the choice of robust optimisation algorithms [7,8].…”

“…Artificial Neural Network was used as robust search algorithm to extract the FC parameters in [21], a slime mould optimisation algorithm was applied in [7], a flower pollination algorithm was applied in [22].…”

A Novel Opposition-Based Arithmetic Optimization Algorithm for Parameter Extraction of PEM Fuel Cell

“…Different meta-heuristic algorithms have been utilized for parameter optimization of PEMFCs such as particle swarm optimization (PSO) [26], genetic algorithm (GA) [27], artificial neural network (ANN) [28], differential evolution (DE) [29], artificial immune system (AIS) [30], artificial bee colony (ABC) [31], bird mating optimization (BMO) [32], biography-based optimization (BMO) [33], seeker optimization algorithm (SOA) [34], backtracking search algorithm (BSA) [35], improved teaching learning-based optimization (ITLBO) [36]. Slime mold algorithm (SMA) [37], moth-flame optimization (MFO) [38], Archimedes optimization algorithm [39], Jellyfish search algorithm (JSA) [40], bonobo optimizer [41], and hybrid GWO algorithm [42] have been implemented to identify the unknown parameters of PEMFC. In this article, the authors have proposed an improved opposition-based arithmetic optimization algorithm for parameter extraction of PEMFC.…”