A review on lifetime prediction of proton exchange membrane fuel cells system
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 …
power converter device in a wide range of applications, especially in the transportation area …
Degradation mechanisms of proton exchange membrane fuel cell under typical automotive operating conditions
The proton exchange membrane (PEM) fuel cell is an ideal automotive power source with
great potential, owing to its high efficiency and zero emissions. However, the durability and …
great potential, owing to its high efficiency and zero emissions. However, the durability and …
Artificial intelligence and numerical models in hybrid renewable energy systems with fuel cells: Advances and prospects
With the rapid advancement of technology in the energy sector and the demand for
sustainable energy practices, the world is aiming at fostering the hydrogen economy and …
sustainable energy practices, the world is aiming at fostering the hydrogen economy and …
A review on prognostics and health management (PHM) methods of lithium-ion batteries
Batteries are prevalent energy providers for modern systems. They can also be regarded as
storage units for renewable and sustainable energy. Failures of batteries can bring huge …
storage units for renewable and sustainable energy. Failures of batteries can bring huge …
State of health estimation of lithium-ion batteries based on multi-health features extraction and improved long short-term memory neural network
Accurate state of health estimation of lithium-ion batteries is essential to enhance the
reliability and safety of a battery system. However, the estimation accuracy based on a data …
reliability and safety of a battery system. However, the estimation accuracy based on a data …
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 …
health management. This paper presents a hybrid deep learning method by combining the …
Hybridization of hybrid structures for time series forecasting: A review
Z Hajirahimi, M Khashei - Artificial Intelligence Review, 2023 - Springer
Achieving the desired accuracy in time series forecasting has become a binding domain,
and developing a forecasting framework with a high degree of accuracy is one of the most …
and developing a forecasting framework with a high degree of accuracy is one of the most …
Deep learning based prognostic framework towards proton exchange membrane fuel cell for automotive application
Currently, the larger-scaled commercialization of fuel cell technology is considerably
impeded by the limited durability of fuel cells. Prognostics and health management (PHM) is …
impeded by the limited durability of fuel cells. Prognostics and health management (PHM) is …
Prognostics methods and degradation indexes of proton exchange membrane fuel cells: A review
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 …
exchange membrane fuel cells (PEMFCs). The advances of PEMFCs prognostics research …
[HTML][HTML] Study of degradation of fuel cell stack based on the collected high-dimensional data and clustering algorithms calculations
Accurate perception of the performance degradation of fuel cell is very important to detect its
health state. However, inconsistent operating conditions of fuel cell vehicles in the test result …
health state. However, inconsistent operating conditions of fuel cell vehicles in the test result …