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A Model-free Combined Energy and Thermal Management Strategy for HEVs Based on Reinforcement-Learning Under Low-Temperature Journal article
Li, Kai, Chen, Hong, Wu, Yuhu, Zhao, Jing, Ding, Shihong, Gao, Jinwu. A Model-free Combined Energy and Thermal Management Strategy for HEVs Based on Reinforcement-Learning Under Low-Temperature[J]. IEEE Transactions on Intelligent Vehicles, 2024.
Authors:  Li, Kai;  Chen, Hong;  Wu, Yuhu;  Zhao, Jing;  Ding, Shihong; et al.
Favorite | TC[Scopus]:0  IF:14.0/11.2 | Submit date：2024/07/04
Batteries  Combined Energy And Thermal Management (C-etm)  Couplings  Deep Reinforcement Learning  Energy Management  Heat Engines  Hybrid Electric Vehicles (Hevs)  Low Temperature Environment  Model-free  Optimization  Thermal Management  Waste Heat  
A Novel Energy Management Strategy for PHEV Considering Cabin Heat Demand Under Low Temperature Based on Reinforcement Learning Journal article
Li, Kai, Chen, Hong, Hou, Shengyan, Eriksson, Lars, Zhao, Jing, Ding, Shihong, Gao, Jinwu. A Novel Energy Management Strategy for PHEV Considering Cabin Heat Demand Under Low Temperature Based on Reinforcement Learning[J]. IEEE Transactions on Transportation Electrification, 2024.
Authors:  Li, Kai;  Chen, Hong;  Hou, Shengyan;  Eriksson, Lars;  Zhao, Jing; et al.
Favorite | TC[Scopus]:0  IF:7.2/7.9 | Submit date：2024/09/03
Batteries  Cabin Heat Demand  Deep Reinforcement Learning  Energy Management  Energy Management System  Fuel Economy  Heat Engines  Heat Pumps  Hybrid Electric Vehicles (Hevs)  Low Temperature Environment  Real-time  Resistance Heating  Waste Heat  
Twin delayed deep deterministic policy gradient based energy management strategy for fuel cell/battery/ultracapacitor hybrid electric vehicles considering predicted terrain information Journal article
Tao, Fazhan, Fu, Zhigao, Gong, Huixian, Ji, Baofeng, Zhou, Yao. Twin delayed deep deterministic policy gradient based energy management strategy for fuel cell/battery/ultracapacitor hybrid electric vehicles considering predicted terrain information[J]. Energy, 2023, 283, 129173.
Authors:  Tao, Fazhan;  Fu, Zhigao;  Gong, Huixian;  Ji, Baofeng;  Zhou, Yao
Favorite | TC[WOS]:6 TC[Scopus]:6  IF:9.0/8.2 | Submit date：2023/12/04
Action Screening Mechanism  Deep Reinforcement Learning  Energy Management Strategy  Fuel Cell Hybrid Electric Vehicle  Predicted Terrain Information  
Deep Reinforcement Learning Empowered Rate Selection of XP-HARQ Journal article
Wu, Da, Feng, Jiahui, Shi, Zheng, Lei, Hongjiang, Yang, Guanghua, Ma, Shaodan. Deep Reinforcement Learning Empowered Rate Selection of XP-HARQ[J]. IEEE Communications Letters, 2023, 27(9), 2363-2367.
Authors:  Wu, Da;  Feng, Jiahui;  Shi, Zheng;  Lei, Hongjiang;  Yang, Guanghua; et al.
Favorite | TC[WOS]:1 TC[Scopus]:2  IF:3.7/3.5 | Submit date：2023/10/10
Cross-packet Hybrid Automatic Repeat Request (Xp-harq)  Deep Reinforcement Learning (Drl)  Outdated Channel State Information  Rate Selection  
Two-Tier Multi-Access Partial Computation Offloading via NOMA: A Hybrid Deep Learning Approach for Energy Minimization Conference paper
Li Yang, Wu Yuan, Bi Suzhi, Qian Liping, Quek Tony Q.S., Xu Chengzhong, Shi Zhiguo. Two-Tier Multi-Access Partial Computation Offloading via NOMA: A Hybrid Deep Learning Approach for Energy Minimization[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2022, 138-143.
Authors:  Li Yang;  Wu Yuan;  Bi Suzhi;  Qian Liping;  Quek Tony Q.S.; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2023/01/30
Hybrid Deep Reinforcement Learning  Non-orthogonal Multiple Access  Two-tier Offloading