[HTML][HTML] Machine learning modeling for proton exchange membrane fuel cell performance

A Legala, J Zhao, X Li - Energy and AI, 2022 - Elsevier
Proton exchange membrane fuel cell (PEMFC) is considered essential for climate change
mitigation, and a fast and accurate model is necessary for its control and operation in …

Performance prediction of proton-exchange membrane fuel cell based on convolutional neural network and random forest feature selection

W Huo, W Li, Z Zhang, C Sun, F Zhou… - Energy Conversion and …, 2021 - Elsevier
For optimizing the performance of the proton exchange membrane fuel cells (PEMFCs), the I–
V polarization curve is generally used as an important evaluation metric, which can …

A data-driven framework for performance prediction and parameter optimization of a proton exchange membrane fuel cell

HW Li, BX Qiao, JN Liu, Y Yang, W Fan… - Energy Conversion and …, 2022 - Elsevier
The optimization of structure and operating conditions for enhancing the performance of
proton exchange membrane fuel cells have attracted much attention. High-precision …

[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 …

Artificial neural network-based model predictive control for optimal operating conditions in proton exchange membrane fuel cells

Y Cho, G Hwang, DQ Gbadago, S Hwang - Journal of Cleaner Production, 2022 - Elsevier
In the large-scale commercialization of proton exchange membrane fuel cells (PEMFC),
efficient control of the dynamic operation requires the consideration of complex …

[HTML][HTML] Parameter identification of PEMFC based on Convolutional neural network optimized by balanced deer hunting optimization algorithm

Z Yuan, W Wang, H Wang, M Ashourian - Energy Reports, 2020 - Elsevier
This paper proposes a new optimal method for the parameter identification of a proton
exchange membrane fuel cell (PEMFC) for increasing the model accuracy. In this research …

Modeling a PEMFC by a support vector machine

ZD Zhong, XJ Zhu, GY Cao - Journal of Power Sources, 2006 - Elsevier
This paper reports a modeling study of proton exchange membrane fuel cell (PEMFC)
performance by using a support vector machine (SVM). A PEMFC is a nonlinear, multi …

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 …

Performance prediction and power density maximization of a proton exchange membrane fuel cell based on deep belief network

HW Li, BS Xu, CH Du, Y Yang - Journal of Power Sources, 2020 - Elsevier
Intelligent methods have become powerful modeling tools for predicting the performance of
complex systems. As one of these methods, the deep belief network (DBN) is employed to …

Optimization of maximum power density output for proton exchange membrane fuel cell based on a data-driven surrogate model

SS Feng, WT Huang, Z Huang, Q Jian - Applied Energy, 2022 - Elsevier
Operating conditions are of great significance for proton exchange membrane fuel cells
(PEMFCs) and directly determine the output performance of PEMFC. In this paper, an …