书目名称 | Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles | 编辑 | Yuecheng Li,Hongwen He | 视频video | | 丛书名称 | Synthesis Lectures on Advances in Automotive Technology | 图书封面 |  | 描述 | The urgent need for vehicle electrification and improvement in fuel efficiency has gained increasing attention worldwide. Regarding this concern, the solution of hybrid vehicle systems has proven its value from academic research and industry applications, where energy management plays a key role in taking full advantage of hybrid electric vehicles (HEVs). There are many well-established energy management approaches, ranging from rules-based strategies to optimization-based methods, that can provide diverse options to achieve higher fuel economy performance. However, the research scope for energy management is still expanding with the development of intelligent transportation systems and the improvement in onboard sensing and computing resources. Owing to the boom in machine learning, especially deep learning and deep reinforcement learning (DRL), research on learning-based energy management strategies (EMSs) is gradually gaining more momentum. They have shown great promise in not onlybeing capable of dealing with big data, but also in generalizing previously learned rules to new scenarios without complex manually tunning. Focusing on learning-based energy management with DRL as the | 出版日期 | Book 2022 | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-79206-9 | isbn_softcover | 978-3-031-79194-9 | isbn_ebook | 978-3-031-79206-9Series ISSN 2576-8107 Series E-ISSN 2576-8131 | issn_series | 2576-8107 | copyright | Springer Nature Switzerland AG 2022 |
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