| 1 |
State-of-charge estimation for LiNi0.6Co0.2Mn0.2O2/graphite batteries using the compound method with improved extended Kalman filter and long short-term memory network
Xu S, Zhou JX, Zhou F, Liu YC
International Journal of Energy Research, 45(4), 6115, 2021 |
| 2 |
State of charge and online model parameters co-estimation for liquid metal batteries
Liu GA, Xu C, Li HM, Jiang K, Wang KL
Applied Energy, 250, 677, 2019 |
| 3 |
Efficiency Extreme Point Tracking Strategy Based on FFRLS Online Identification for PEMFC System
Wang TH, Li Q, Qiu YB, Yin LZ, Liu L, Chen WR
IEEE Transactions on Energy Conversion, 34(2), 952, 2019 |
| 4 |
Hydrogen consumption minimization method based on the online identification for multi-stack PEMFCs system
Wang TH, Li Q, Yin LZ, Chen WR
International Journal of Hydrogen Energy, 44(11), 5074, 2019 |
| 5 |
Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle
Xiong R, Cao JY, Yu QQ
Applied Energy, 211, 538, 2018 |
| 6 |
A computationally reduced version of the fast H-infinity filter
Nishiyama K
Automatica, 92, 249, 2018 |
| 7 |
Recursive subspace identification subject to relatively slow time-varying load disturbance
Hou J, Liu T, Wang QG
International Journal of Control, 91(3), 622, 2018 |
| 8 |
H-infinity optimality and a posteriori output estimate of the forgetting factor NLMS algorithm
Nishiyama K
Automatica, 75, 244, 2017 |
| 9 |
Adaptive hysteresis compensation on an experimental nanopositioning platform
Ryba L, Dokoupil J, Voda A, Besancon G
International Journal of Control, 90(4), 765, 2017 |
| 10 |
Identification of discrete-time output error model for industrial processes with time delay subject to load disturbance
Dong SJ, Liu T, Wang W, Bao J, Cao Y
Journal of Process Control, 50, 40, 2017 |
