TY - JOUR
KW - Parameter Estimation
KW - Proton Exchange Membrane Fuel Cell
KW - Tree Growth Algorithm
KW - Total of the Squared Deviations (TSD)
AU - Salah Kamel
AU - Francisco Jurado
AU - Hamdy Sultan
AU - Ahmed Menesy
AB - Demonstrating an accurate mathematical model is a mandatory issue for realistic simulation, optimization and performance evaluation of proton exchange membrane fuel cells (PEMFCs). The main goal of this study is to demonstrate a precise mathematical model of PEMFCs through estimating the optimal values of the unknown parameters of these cells. In this paper, an efficient optimization technique, namely, Tree Growth Algorithm (TGA) is applied for extracting the optimal parameters of different PEMFC stacks. The total of the squared deviations (TSD) between the experimentally measured data and the estimated ones is adopted as the objective function. The effectiveness of the developed parameter identification algorithm is validated through four case studies of commercial PEMFC stacks under various operating conditions. Moreover, comprehensive comparisons with other optimization algorithms under the same study cases are demonstrated. Statistical analysis is presented to evaluate the accuracy and reliability of the developed algorithm in solving the studied optimization problem.
IS - Regular Issue
M1 - 2
N2 - Demonstrating an accurate mathematical model is a mandatory issue for realistic simulation, optimization and performance evaluation of proton exchange membrane fuel cells (PEMFCs). The main goal of this study is to demonstrate a precise mathematical model of PEMFCs through estimating the optimal values of the unknown parameters of these cells. In this paper, an efficient optimization technique, namely, Tree Growth Algorithm (TGA) is applied for extracting the optimal parameters of different PEMFC stacks. The total of the squared deviations (TSD) between the experimentally measured data and the estimated ones is adopted as the objective function. The effectiveness of the developed parameter identification algorithm is validated through four case studies of commercial PEMFC stacks under various operating conditions. Moreover, comprehensive comparisons with other optimization algorithms under the same study cases are demonstrated. Statistical analysis is presented to evaluate the accuracy and reliability of the developed algorithm in solving the studied optimization problem.
PY - 2020
SE - 101
EP - 11
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Tree Growth Algorithm for Parameter Identification of Proton Exchange Membrane Fuel Cell Models
UR - https://www.ijimai.org/journal/sites/default/files/2020-05/ijimai_6_2_11.pdf
VL - 6
SN - 1989-1660
ER -