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 …

[HTML][HTML] Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology

Y Wang, B Seo, B Wang, N Zamel, K Jiao, XC Adroher - Energy and AI, 2020 - Elsevier
Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly
convert the chemical energy stored in fuel into electrical energy with a practical conversion …

A systematic review of machine learning methods applied to fuel cells in performance evaluation, durability prediction, and application monitoring

W Ming, P Sun, Z Zhang, W Qiu, J Du, X Li… - International Journal of …, 2023 - Elsevier
A fuel cell is a power generation device that directly converts chemical energy into electrical
energy through chemical reactions; fuel cells are widely used in aerospace, electric vehicle …

Fuel cell electric vehicles—A brief review of current topologies and energy management strategies

IS Sorlei, N Bizon, P Thounthong, M Varlam… - Energies, 2021 - mdpi.com
With the development of technologies in recent decades and the imposition of international
standards to reduce greenhouse gas emissions, car manufacturers have turned their …

Taxonomy research of artificial intelligence for deterministic solar power forecasting

H Wang, Y Liu, B Zhou, C Li, G Cao, N Voropai… - Energy Conversion and …, 2020 - Elsevier
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …

A novel adaptive discrete grey model with time-varying parameters for long-term photovoltaic power generation forecasting

S Ding, R Li, Z Tao - Energy Conversion and Management, 2021 - Elsevier
The rapidly growing photovoltaic power generation (PPG) instigates stochastic volatility of
electricity supply that may compromise the power grid's stability and increase the grid …

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 …

[HTML][HTML] Advances of machine learning in multi-energy district communities‒mechanisms, applications and perspectives

Y Zhou - Energy and AI, 2022 - Elsevier
Energy paradigm transition towards the carbon neutrality requires combined and continuous
efforts in cleaner power production, advanced energy storages, flexible district energy …

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 …

Evolutionary gate recurrent unit coupling convolutional neural network and improved manta ray foraging optimization algorithm for performance degradation …

Z Tao, C Zhang, J **ong, H Hu, J Ji, T Peng, MS Nazir - Applied Energy, 2023 - Elsevier
Performance degradation prediction is an effective method to improve the durability of
proton exchange membrane fuel cell (PEMFC). In this study, a hybrid deep learning model …