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 | 424 | 2019 |
State-of-charge estimation of lithium-ion batteries using LSTM and UKF F Yang, S Zhang, W Li, Q Miao Energy 201, 117664, 2020 | 325 | 2020 |
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 | 311 | 2018 |
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 | 262 | 2016 |
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 | 256 | 2019 |
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 | 223 | 2016 |
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 | 192 | 2019 |
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 | 163 | 2021 |
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 | 153 | 2020 |
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 | 145 | 2019 |
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 | 123 | 2019 |
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 | 121 | 2021 |
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 | 119 | 2017 |
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 | 117 | 2021 |
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 | 99 | 2017 |
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 | 94 | 2020 |
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 | 89 | 2019 |
Battery remaining useful life prediction at different discharge rates D Wang, F Yang, Y Zhao, KL Tsui Microelectronics Reliability 78, 212-219, 2017 | 84 | 2017 |
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 | 67 | 2020 |
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 | 62 | 2020 |