Energies | |
Reinforcement Learning–Based Energy Management Strategy for a Hybrid Electric Tracked Vehicle | |
Teng Liu2  Yuan Zou1  Dexing Liu2  Fengchun Sun2  Joeri Van Mierlo2  Ming Cheng2  Omar Hegazy2  | |
[1] Collaborative Innovation Center of Electric Vehicles in Beijing, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China; | |
关键词:
reinforcement learning (RL);
hybrid electric tracked vehicle (HETV);
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DOI : 10.3390/en8077243 | |
来源: mdpi | |
【 摘 要 】
This paper presents a reinforcement learning (RL)–based energy management strategy for a hybrid electric tracked vehicle. A control-oriented model of the powertrain and vehicle dynamics is first established. According to the sample information of the experimental driving schedule, statistical characteristics at various velocities are determined by extracting the transition probability matrix of the power request. Two RL-based algorithms, namely
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190009248ZK.pdf | 783KB | download |