Enabling cross-type full-knowledge transferable energy management for hybrid electric vehicles via deep transfer reinforcement learning-Reference-Cited by-同舟云学术

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Enabling cross-type full-knowledge transferable energy management for hybrid electric vehicles via deep transfer reinforcement learning

Published:2024-10 Issue: Volume:305 Page:132394
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Huang Ruchen,He Hongwen,Su Qicong,Härtl Martin,Jaensch Malte^ORCID

Publisher

Elsevier BV

Reference52 articles.

1. Recent advances in urban green energy development towards carbon emissions neutrality;Woon;Energy,2023

2. Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets;Zhao;Energy,2023

3. Naturalistic data-driven and emission reduction-conscious energy management for hybrid electric vehicle based on improved soft actor-critic algorithm;Huang;J Power Sources,2023

4. A novel hierarchical predictive energy management strategy for plug-in hybrid electric bus combined with deep deterministic policy gradient;He;J Energy Storage,2022

5. Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle;Lian;Energy,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An intelligent full-knowledge transferable collaborative eco-driving framework based on improved soft actor-critic algorithm;Applied Energy;2024-12

2. Smart energy management for hybrid electric bus via improved soft actor-critic algorithm in a heuristic learning framework;Energy;2024-11

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