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 …

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 …

Well production forecasting based on ARIMA-LSTM model considering manual operations

D Fan, H Sun, J Yao, K Zhang, X Yan, Z Sun - Energy, 2021 - Elsevier
Accurate and efficient prediction of well production is essential for extending a well's life
cycle and improving reservoir recovery. Traditional models require expensive computational …

Model prediction control-based energy management combining self-trending prediction and subset-searching algorithm for hydrogen electric multiple unit train

Q Li, P Liu, X Meng, G Zhang, Y Ai… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
To apply the actual fuel cell hybrid system, improve the efficiency of fuel cells, and reduce
the operating cost, the model predictive control (MPC)-based energy management strategy …

A data-driven method for multi-step-ahead prediction and long-term prognostics of proton exchange membrane fuel cell

K Benaggoune, M Yue, S Jemei, N Zerhouni - Applied Energy, 2022 - Elsevier
Fuel cell technology has been rapidly developed in the last decade owing to its clean
characteristic and high efficiency. Proton exchange membrane fuel cells (PEMFCs) are …

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 …

Approximate cost-optimal energy management of hydrogen electric multiple unit trains using double Q-learning algorithm

Q Li, X Meng, F Gao, G Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Energy management strategy (EMS) is the key to the performance of fuel cell/battery hybrid
system. At present, reinforcement learning (RL) has been introduced into this field and has …

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 …

Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load

C Wang, M Dou, Z Li, R Outbib, D Zhao, J Zuo… - Reliability Engineering & …, 2023 - Elsevier
Data-centric prognostics is beneficial to improve the reliability and safety of proton exchange
membrane fuel cell (PEMFC). For the prognostics of PEMFC operating under dynamic load …