A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Precise Modeling of Proton Exchange Membrane Fuel Cell Using the Modified Bald Eagle Optimization Algorithm
The proton exchange membrane fuel cell (PEMFC) is a green energy converter that is based on the chemical reaction process. The behavior of this system can change with time due to aging and operating conditions. Knowing the current state of this system requires an accurate model, and an exact PEMFC model requires precise parameters. These parameters should be identified and used to properly fit the polarization curve in order to effectively replicate the PEMFC behavior. This work suggests a precise unknown PEMFC parameter extraction based on a new metaheuristic optimization algorithm called the modified bald eagle search algorithm (mBES). The mBES is an optimization algorithm based on the principles of bald eagle behavior that combines local search and global search to achieve a balance between the exploration and exploitation of search spaces. It is a powerful and efficient technique for optimization problems where accurate and near-optimal solutions are desired. To approve the accuracy of the proposed identification approach, the proposed algorithm is compared to the following metaheuristic algorithms: bald eagle search algorithm (BES), artificial ecosystem-based optimization (AEO), leader Harris Hawk’s optimization (LHHO), rain optimization algorithm (ROA), sine cosine algorithm (SCA), and salp swarm algorithm (SSA). This evaluation process is applied to two commercialized PEMFC stacks: BCS 500 W PEMFC and Avista SR-12 PEM. The extracted parameters’ accuracy is measured as the sum of square errors (SSE) between the results produced by the optimizer and the experimental data in the objective function. As a result, the proposed PEMFC optimizing model outperforms the comparison models in terms of system correctness and convergence. The proposed extraction strategy, mBES, obtained the best results, with a fitness value of 0.011364 for the 500 W BCS and 0.035099 for the Avista SR-12 500 W PEMFC.
Precise Modeling of Proton Exchange Membrane Fuel Cell Using the Modified Bald Eagle Optimization Algorithm
The proton exchange membrane fuel cell (PEMFC) is a green energy converter that is based on the chemical reaction process. The behavior of this system can change with time due to aging and operating conditions. Knowing the current state of this system requires an accurate model, and an exact PEMFC model requires precise parameters. These parameters should be identified and used to properly fit the polarization curve in order to effectively replicate the PEMFC behavior. This work suggests a precise unknown PEMFC parameter extraction based on a new metaheuristic optimization algorithm called the modified bald eagle search algorithm (mBES). The mBES is an optimization algorithm based on the principles of bald eagle behavior that combines local search and global search to achieve a balance between the exploration and exploitation of search spaces. It is a powerful and efficient technique for optimization problems where accurate and near-optimal solutions are desired. To approve the accuracy of the proposed identification approach, the proposed algorithm is compared to the following metaheuristic algorithms: bald eagle search algorithm (BES), artificial ecosystem-based optimization (AEO), leader Harris Hawk’s optimization (LHHO), rain optimization algorithm (ROA), sine cosine algorithm (SCA), and salp swarm algorithm (SSA). This evaluation process is applied to two commercialized PEMFC stacks: BCS 500 W PEMFC and Avista SR-12 PEM. The extracted parameters’ accuracy is measured as the sum of square errors (SSE) between the results produced by the optimizer and the experimental data in the objective function. As a result, the proposed PEMFC optimizing model outperforms the comparison models in terms of system correctness and convergence. The proposed extraction strategy, mBES, obtained the best results, with a fitness value of 0.011364 for the 500 W BCS and 0.035099 for the Avista SR-12 500 W PEMFC.
Precise Modeling of Proton Exchange Membrane Fuel Cell Using the Modified Bald Eagle Optimization Algorithm
Alaa A. Zaky (author) / Rania M. Ghoniem (author) / F. Selim (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Pacific Bald Eagle Recovery Plan
NTIS | 1986
Location of Logistics Distribution Center Based on Improved Bald Eagle Algorithm
| DOAJ | 2022
Proton Exchange Membrane Fuel Cells Modeling Using Chaos Game Optimization Technique
| DOAJ | 2021
Optimization of a proton exchange membrane fuel cell membrane electrode assembly
| British Library Online Contents | 2010