A review on lifetime prediction of proton exchange membrane fuel cells system

Z Hua, Z Zheng, E Pahon, MC Péra, F Gao - Journal of Power Sources, 2022 - Elsevier
The proton exchange membrane fuel cells (PEMFC) system is a promising eco-friendly
power converter device in a wide range of applications, especially in the transportation area …

Prognostics methods and degradation indexes of proton exchange membrane fuel cells: A review

H Liu, J Chen, D Hissel, J Lu, M Hou, Z Shao - Renewable and Sustainable …, 2020 - Elsevier
Prognostics is a promising solution to the short lifetime and high-cost bottlenecks of proton
exchange membrane fuel cells (PEMFCs). The advances of PEMFCs prognostics research …

Data-driven proton exchange membrane fuel cell degradation predication through deep learning method

R Ma, T Yang, E Breaz, Z Li, P Briois, F Gao - Applied energy, 2018 - Elsevier
Proton exchange membrane fuel cells (PEMFCs) is one of the principal candidates to take
part of the worldwide future clean and renewable energy solution. However, fuel cells are …

Short-term performance degradation prediction of a commercial vehicle fuel cell system based on CNN and LSTM hybrid neural network

B Sun, X Liu, J Wang, X Wei, H Yuan, H Dai - International Journal of …, 2023 - Elsevier
Short-term performance degradation prediction is significant for fuel cell system control and
health management. This paper presents a hybrid deep learning method by combining the …

Remaining useful life prediction of PEMFC systems under dynamic operating conditions

Z Hua, Z Zheng, E Pahon, MC Péra, F Gao - Energy Conversion and …, 2021 - Elsevier
Abstract The Prognostic and Health Management (PHM) has been developed for more than
two decades. It is capable to anticipate the impending failures and make decisions in …

Degradation prediction of proton exchange membrane fuel cell based on grey neural network model and particle swarm optimization

K Chen, S Laghrouche, A Djerdir - Energy Conversion and Management, 2019 - Elsevier
The degradation prediction is an effective tool for the long-lasting operation of the proton
exchange membrane fuel cells (PEMFC). In this paper, a novel grey neural network model …

A hybrid remaining useful life prognostic method for proton exchange membrane fuel cell

Y Cheng, N Zerhouni, C Lu - International Journal of Hydrogen Energy, 2018 - Elsevier
Abstract Proton Exchange Membrane Fuel Cell (PEMFC) has become a promising power
source with wide applications to many electronic and electrical devices. However, even if it …

Review on hydrogen fuel cell condition monitoring and prediction methods

RH Lin, XN Xi, PN Wang, BD Wu, SM Tian - International Journal of …, 2019 - Elsevier
A hydrogen fuel cell combines oxygen and hydrogen to generate electricity, which becomes
a promising power source. The conditions of the fuel cell, such as health status, and faults …

Degradation model of proton exchange membrane fuel cell based on a novel hybrid method

K Chen, S Laghrouche, A Djerdir - Applied Energy, 2019 - Elsevier
This paper proposes a new hybrid degradation model of Proton Exchange Membrane Fuel
Cell (PEMFC) used in Fuel Cell Electric Vehicle (FCEV) operating under real conditions …

Comparison of echo state network and feed-forward neural networks in electrical load forecasting for demand response programs

M Mansoor, F Grimaccia, S Leva, M Mussetta - … and Computers in …, 2021 - Elsevier
The electrical load forecasting is a fundamental technique for consumer load prediction for
utilities. The accurate load forecasting is crucial to design Demand Response (DR) …