2022
DOI: 10.1007/s40684-022-00476-2
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Recent Progress in Learning Algorithms Applied in Energy Management of Hybrid Vehicles: A Comprehensive Review

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Cited by 21 publications
(2 citation statements)
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“…The emergence of DRL algorithm solves the problem of the traditional RL algorithm's tendency to fall into the dimensionality catastrophe due to discretization. Currently, the mainstream of DRL is discrete reinforcement learning and continuous reinforcement learning [21], [22]. In the case of continuous problems, the action space of discrete reinforcement learning is limited, so it is necessary to discretize continuous actions.…”
Section: A Literature Reviewmentioning
confidence: 99%
“…The emergence of DRL algorithm solves the problem of the traditional RL algorithm's tendency to fall into the dimensionality catastrophe due to discretization. Currently, the mainstream of DRL is discrete reinforcement learning and continuous reinforcement learning [21], [22]. In the case of continuous problems, the action space of discrete reinforcement learning is limited, so it is necessary to discretize continuous actions.…”
Section: A Literature Reviewmentioning
confidence: 99%
“…Xu [ 9 ] conducted a classification and comprehensive overview of energy management strategies for hybrid electric vehicles from the perspectives of reinforcement learning and deep learning. Additionally, the strengths and weaknesses of different learning algorithms were discussed.…”
Section: Introductionmentioning
confidence: 99%