Battery-degradation-involved energy management strategy based on deep reinforcement learning for fuel cell/battery/ultracapacitor hybrid electric vehicle

[1]  Fazhan Tao,et al.  Driving-Behavior-Aware Optimal Energy Management Strategy for Multi-Source Fuel Cell Hybrid Electric Vehicles Based on Adaptive Soft Deep-Reinforcement Learning , 2023, IEEE Transactions on Intelligent Transportation Systems.

[2]  Hao Wang,et al.  Energy Management Strategy for Fuel Cell/Battery/Ultracapacitor Hybrid Electric Vehicles Using Deep Reinforcement Learning With Action Trimming , 2022, IEEE Transactions on Vehicular Technology.

[3]  Amar Kumar Barik,et al.  Integrated resource planning in sustainable energy-based distributed microgrids , 2021, Sustainable Energy Technologies and Assessments.

[4]  Mehmet Hakan Demir,et al.  A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects , 2021 .

[5]  Fazhan Tao,et al.  Data-driven reinforcement-learning-based hierarchical energy management strategy for fuel cell/battery/ultracapacitor hybrid electric vehicles , 2020, Journal of Power Sources.

[6]  Amir Khajepour,et al.  Energy management for a power-split hybrid electric bus via deep reinforcement learning with terrain information , 2019 .

[7]  Jiankun Peng,et al.  Energy management of hybrid electric bus based on deep reinforcement learning in continuous state and action space , 2019, Energy Conversion and Management.

[8]  Hongwen He,et al.  Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus , 2019, Applied Energy.

[9]  Alexandre Ravey,et al.  Online adaptive equivalent consumption minimization strategy for fuel cell hybrid electric vehicle considering power sources degradation , 2019, Energy Conversion and Management.

[10]  Hongwen He,et al.  Deep Reinforcement Learning-Based Energy Management for a Series Hybrid Electric Vehicle Enabled by History Cumulative Trip Information , 2019, IEEE Transactions on Vehicular Technology.

[11]  Yan Xu,et al.  Data-Driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method With Continuous Action Search , 2019, IEEE Transactions on Power Systems.

[12]  Alexandre Ravey,et al.  A novel equivalent consumption minimization strategy for hybrid electric vehicle powered by fuel cell, battery and supercapacitor , 2018, Journal of Power Sources.

[13]  Hongwen He,et al.  Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus , 2018, Applied Energy.

[14]  Arzu Turksoy,et al.  Analysis of the control strategies for fuel saving in the hydrogen fuel cell vehicles , 2018, International Journal of Hydrogen Energy.

[15]  Hong Chen,et al.  Acceleration Speed Optimization of Intelligent EVs in Consideration of Battery Aging , 2018, IEEE Transactions on Vehicular Technology.

[16]  Xiang Cheng,et al.  Critical issues of energy efficient and new energy vehicles development in China , 2018 .

[17]  Rui Xiong,et al.  Reinforcement Learning-based Real-time Energy Management for Plug-in Hybrid Electric Vehicle with Hybrid Energy Storage System , 2017 .

[18]  Yanjun Huang,et al.  Model predictive control power management strategies for HEVs: A review , 2017 .

[19]  Simona Onori,et al.  A control-oriented cycle-life model for hybrid electric vehicle lithium- ion batteries , 2016 .

[20]  Joao P. S. Catalao,et al.  New control strategy for the weekly scheduling of insular power systems with a battery energy storage system , 2015 .

[21]  Yuan Zou,et al.  Reinforcement Learning of Adaptive Energy Management With Transition Probability for a Hybrid Electric Tracked Vehicle , 2015, IEEE Transactions on Industrial Electronics.

[22]  Chao Yang,et al.  Correctional DP-Based Energy Management Strategy of Plug-In Hybrid Electric Bus for City-Bus Route , 2015, IEEE Transactions on Vehicular Technology.

[23]  Heath Hofmann,et al.  Energy management strategies comparison for electric vehicles with hybrid energy storage system , 2014 .

[24]  Dirk Uwe Sauer,et al.  A holistic aging model for Li(NiMnCo)O2 based 18650 lithium-ion batteries , 2014 .

[25]  Jianqiu Li,et al.  Application of Pontryagin's Minimal Principle to the energy management strategy of plugin fuel cell electric vehicles , 2013 .

[26]  Jianqiu Li,et al.  Real time optimal energy management strategy targeting at minimizing daily operation cost for a plug-in fuel cell city bus , 2012 .

[27]  M. Verbrugge,et al.  Cycle-life model for graphite-LiFePO 4 cells , 2011 .

[28]  Zhihong Yu,et al.  An innovative optimal power allocation strategy for fuel cell, battery and supercapacitor hybrid electric vehicle , 2011 .

[29]  Bernard Davat,et al.  Energy Management of a Fuel Cell/Supercapacitor/Battery Power Source for Electric Vehicular Applications , 2011, IEEE Transactions on Vehicular Technology.

[30]  Abdellatif Miraoui,et al.  A Multiphysic Dynamic 1-D Model of a Proton-Exchange-Membrane Fuel-Cell Stack for Real-Time Simulation , 2010, IEEE Transactions on Industrial Electronics.

[31]  Alireza Khaligh,et al.  Battery, Ultracapacitor, Fuel Cell, and Hybrid Energy Storage Systems for Electric, Hybrid Electric, Fuel Cell, and Plug-In Hybrid Electric Vehicles: State of the Art , 2010, IEEE Transactions on Vehicular Technology.

[32]  Hiroyuki Katsukawa,et al.  Degradation Mechanism and Life Prediction of Lithium-Ion Batteries , 2006 .

[33]  Ralph E. White,et al.  Development of First Principles Capacity Fade Model for Li-Ion Cells , 2004 .

[34]  Weida Wang,et al.  Longevity-conscious energy management strategy of fuel cell hybrid electric Vehicle Based on deep reinforcement learning , 2022 .

[35]  C. Su,et al.  Research on energy management strategy of fuel cell–battery–supercapacitor passenger vehicle , 2022, Energy Reports.

[36]  Fengchun Sun,et al.  Investigating adaptive-ECMS with velocity forecast ability for hybrid electric vehicles , 2017 .