Urmăriți
Fangfang YANG
Fangfang YANG
Associate Professor, Sun Yat-sen University
Adresă de e-mail confirmată pe mail.sysu.edu.cn
Titlu
Citat de
Citat de
Anul
State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network
F Yang, W Li, C Li, Q Miao
Energy 175, 66-75, 2019
4622019
State-of-charge estimation of lithium-ion batteries using LSTM and UKF
F Yang, S Zhang, W Li, Q Miao
Energy 201, 117664, 2020
3692020
A study of the relationship between coulombic efficiency and capacity degradation of commercial lithium-ion batteries
F Yang, D Wang, Y Zhao, KL Tsui, SJ Bae
Energy 145, 486-495, 2018
3372018
Remaining useful life prediction of lithium-ion batteries based on spherical cubature particle filter
D Wang, F Yang, KL Tsui, Q Zhou, SJ Bae
IEEE Transactions on Instrumentation and Measurement 65 (6), 1282-1291, 2016
2852016
Combined CNN-LSTM network for state-of-charge estimation of lithium-ion batteries
X Song, F Yang, D Wang, KL Tsui
IEEE Access 7, 88894 - 88902, 2019
2842019
A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile
F Yang, Y Xing, D Wang, KL Tsui
Applied energy 164, 387-399, 2016
2332016
State-of-charge estimation of lithium-ion batteries via long short-term memory network
F Yang, X Song, F Xu, KL Tsui
IEEE Access 7, 53792 - 53799, 2019
2152019
Early prediction of battery lifetime via a machine learning based framework
Z Fei, F Yang, KL Tsui, L Li, Z Zhang
Energy 225, 120205, 2021
2022021
Lifespan prediction of lithium-ion batteries based on various extracted features and gradient boosting regression tree model
F Yang, D Wang, F Xu, Z Huang, KL Tsui
Journal of Power Sources 476, 228654, 2020
1832020
Convolutional gated recurrent unit -recurrent neural network for state-of-charge estimation of lithium-ion batteries
Z Huang,F Yang, F Xu, X Song, KL Tsui
IEEE Access, 2019
1672019
Voltage-temperature health feature extraction to improve prognostics and health management of lithium-ion batteries
J Kong, F Yang, X Zhang, E Pan, Z Peng, D Wang
Energy 223, 120114, 2021
1462021
A coulombic efficiency-based model for prognostics and health estimation of lithium-ion batteries
F Yang, X Song, G Dong, KL Tsui
Energy 171, 1173-1182, 2019
1392019
Life prediction of lithium-ion batteries based on stacked denoising autoencoders
F Xu, F Yang, Z Fei, Z Huang, KL Tsui
Reliability Engineering & System Safety 208, 107396, 2021
1382021
Prognostics of Li (NiMnCo) O2-based lithium-ion batteries using a novel battery degradation model
F Yang, D Wang, Y Xing, KL Tsui
Microelectronics Reliability 70, 70-78, 2017
1282017
Battery state of health modeling and remaining useful life prediction through time series model
CP Lin, J Cabrera, F Yang, MH Ling, KL Tsui, SJ Bae
Applied Energy 275, 115338, 2020
1122020
Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries
D Wang, Y Zhao, F Yang, KL Tsui
Mechanical Systems and Signal Processing 93, 531-544, 2017
982017
Data-driven battery health prognosis using adaptive Brownian motion model
G Dong, F Yang, Z Wei, J Wei, KL Tsui
IEEE Transactions on Industrial Informatics 16 (7), 4736-4746, 2019
962019
Battery remaining useful life prediction at different discharge rates
D Wang, F Yang, Y Zhao, KL Tsui
Microelectronics Reliability 78, 212-219, 2017
882017
Constructing a health indicator for roller bearings by using a stacked auto-encoder with an exponential function to eliminate concussion
F Xu, Z Huang, F Yang, D Wang, KL Tsui
Applied Soft Computing 89, 106119, 2020
772020
Active balancing of lithium-ion batteries using graph theory and A-star search algorithm
G Dong, F Yang, KL Tsui, C Zou
IEEE Transactions on Industrial Informatics 17 (4), 2587-2599, 2020
712020
Sistemul nu poate realiza operația în acest moment. Încercați din nou mai târziu.
Articole 1–20