| 1 |
Self-learning energy management for plug-in hybrid electric bus considering expert experience and generalization performance
Guo HQ, Zhao FR, Guo HL, Cui QH, Du EL, Zhang K
International Journal of Energy Research, 44(7), 5659, 2020 |
| 2 |
Pontryagin's Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus
Xie SB, Hu XS, Xin ZK, Brighton J
Applied Energy, 236, 893, 2019 |
| 3 |
Receding horizon control-based energy management for plug-in hybrid electric buses using a predictive model of terminal SOC constraint in consideration of stochastic vehicle mass
Guo HQ, Lu SL, Hui HZ, Bao CJ, Shangguan JY
Energy, 176, 292, 2019 |
| 4 |
Optimal rule design methodology for energy management strategy of a power-split hybrid electric bus
Wang Y, Zeng XH, Song DF, Yang NN
Energy, 185, 1086, 2019 |
| 5 |
Energy management of hybrid electric bus based on deep reinforcement learning in continuous state and action space
Tan HC, Zhang HL, Peng JK, Jiang ZX, Wu YK
Energy Conversion and Management, 195, 548, 2019 |
| 6 |
Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus
Wu JD, He HW, Peng JK, Li YC, Li ZJ
Applied Energy, 222, 799, 2018 |
| 7 |
Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system
Du JY, Zhang XB, Wang TZ, Song ZY, Yang XQ, Wang HW, Ouyang MG, Wu XG
Energy, 165, 153, 2018 |
| 8 |
Rule based energy management strategy for a series-parallel plug-in hybrid electric bus optimized by dynamic programming
Peng JK, He HW, Xiong R
Applied Energy, 185, 1633, 2017 |
| 9 |
An energy management strategy based on stochastic model predictive control for plug-in hybrid electric buses
Xie SS, He HW, Peng JK
Applied Energy, 196, 279, 2017 |
| 10 |
Cloud computing-based energy optimization control framework for plug-in hybrid electric bus
Yang C, Li L, You SX, Yan BJ, Du X
Energy, 125, 11, 2017 |
