| 1 |
An indirect RUL prognosis for lithium-ion battery under vibration stress using Elman neural network
Li WH, Jiao ZP, Du L, Fan WY, Zhu YZ
International Journal of Hydrogen Energy, 44(23), 12270, 2019 |
| 2 |
Prognostics of PEM fuel cells based on Gaussian process state space models
Zhu L, Chen JH
Energy, 149, 63, 2018 |
| 3 |
Online remaining useful lifetime prediction of proton exchange membrane fuel cells using a novel robust methodology
Zhou DM, Al-Durra A, Zhang K, Ravey A, Gao F
Journal of Power Sources, 399, 314, 2018 |
| 4 |
A prediction method for the real-time remaining useful life of wind turbine bearings based on the Wiener process
Hu YG, Li H, Shi PP, Chai ZS, Wang K, Xie XJ, Chen Z
Renewable Energy, 127, 452, 2018 |
| 5 |
State of health estimation and remaining useful life prediction of solid oxide fuel cell stack
Dolenc B, Boskoski P, Stepancic M, Pohjoranta A, Juricic D
Energy Conversion and Management, 148, 993, 2017 |
| 6 |
A novel health indicator for PEMFC state of health estimation and remaining useful life prediction
Chen JY, Zhou D, Lyu C, Lu C
International Journal of Hydrogen Energy, 42(31), 20230, 2017 |
| 7 |
Life extension decision making of safety critical systems: An overview
Shafiee M, Animah I
Journal of Loss Prevention in The Process Industries, 47, 174, 2017 |
| 8 |
Lithium-ion battery state of health monitoring and remaining useful life prediction based on support vector regression-particle filter
Dong HC, Jin XN, Lou YB, Wang CH
Journal of Power Sources, 271, 114, 2014 |
| 9 |
A review on prognostics and health monitoring of Li-ion battery
Zhang JL, Lee J
Journal of Power Sources, 196(15), 6007, 2011 |
