| Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming J Peng, H He, R Xiong Applied Energy 185, 1633-1643, 2017 | 718 | 2017 |
| Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus J Wu, H He, J Peng, Y Li, Z Li Applied energy 222, 799-811, 2018 | 410 | 2018 |
| Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus Y Wu, H Tan, J Peng, H Zhang, H He Applied energy 247, 454-466, 2019 | 317 | 2019 |
| Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle R Lian, J Peng, Y Wu, H Tan, H Zhang Energy 197, 117297, 2020 | 279 | 2020 |
| Energy management based on reinforcement learning with double deep Q-learning for a hybrid electric tracked vehicle X Han, H He, J Wu, J Peng, Y Li Applied Energy 254, 113708, 2019 | 246 | 2019 |
| An energy management strategy based on stochastic model predictive control for plug-in hybrid electric buses S Xie, H He, J Peng Applied energy 196, 279-288, 2017 | 219 | 2017 |
| An improved state of charge estimation method based on cubature Kalman filter for lithium-ion batteries J Peng, J Luo, H He, B Lu Applied energy 253, 113520, 2019 | 191 | 2019 |
| A novel MPC-based adaptive energy management strategy in plug-in hybrid electric vehicles G Jinquan, H Hongwen, P Jiankun, Z Nana Energy 175, 378-392, 2019 | 186 | 2019 |
| Deep reinforcement learning-based energy management for a series hybrid electric vehicle enabled by history cumulative trip information Y Li, H He, J Peng, H Wang IEEE Transactions on Vehicular Technology 68 (8), 7416-7430, 2019 | 178 | 2019 |
| Energy management of hybrid electric bus based on deep reinforcement learning in continuous state and action space H Tan, H Zhang, J Peng, Z Jiang, Y Wu Energy Conversion and Management 195, 548-560, 2019 | 169 | 2019 |
| Energy management for a power-split hybrid electric bus via deep reinforcement learning with terrain information Y Li, H He, A Khajepour, H Wang, J Peng Applied Energy 255, 113762, 2019 | 165 | 2019 |
| Real-time estimation of battery state-of-charge with unscented Kalman filter and RTOS μCOS-II platform H He, R Xiong, J Peng Applied energy 162, 1410-1418, 2016 | 149 | 2016 |
| Cross-type transfer for deep reinforcement learning based hybrid electric vehicle energy management R Lian, H Tan, J Peng, Q Li, Y Wu IEEE Transactions on Vehicular Technology 69 (8), 8367-8380, 2020 | 128 | 2020 |
| Hybrid electric vehicle energy management with computer vision and deep reinforcement learning Y Wang, H Tan, Y Wu, J Peng IEEE Transactions on Industrial Informatics 17 (6), 3857-3868, 2020 | 121 | 2020 |
| Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles H Hongwen, G Jinquan, P Jiankun, T Huachun, S Chao Energy 152, 95-107, 2018 | 106 | 2018 |
| Predictive air-conditioner control for electric buses with passenger amount variation forecast☆ H He, M Yan, C Sun, J Peng, M Li, H Jia Applied energy 227, 249-261, 2018 | 79 | 2018 |
| Deep learning for vehicle speed prediction M Yan, M Li, H He, J Peng Energy Procedia 152, 618-623, 2018 | 76 | 2018 |
| A rule-based energy management strategy for a plug-in hybrid school bus based on a controller area network bus J Peng, H Fan, H He, D Pan Energies 8 (6), 5122-5142, 2015 | 70 | 2015 |
| An acceleration slip regulation strategy for four-wheel drive electric vehicles based on sliding mode control H He, J Peng, R Xiong, H Fan Energies 7 (6), 3748-3763, 2014 | 70 | 2014 |
| A deep reinforcement learning-based energy management framework with Lagrangian relaxation for plug-in hybrid electric vehicle H Zhang, J Peng, H Tan, H Dong, F Ding IEEE Transactions on Transportation Electrification 7 (3), 1146-1160, 2020 | 60 | 2020 |
HE Hongwen 何洪文Professor of Mechanical Engineering,Beijing Institute of Technology北京理工大学ایمیل تأیید شده در bit.edu.cn
