Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning
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Title
Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning
Authors
Keywords
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Journal
Applied Sciences-Basel
Volume 8, Issue 2, Pages 187
Publisher
MDPI AG
Online
2018-01-29
DOI
10.3390/app8020187
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- Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective
- (2017) Clara Marina Martinez et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
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- Stochastic Dynamic Programming in the Real-World Control of Hybrid Electric Vehicles
- (2016) Christopher Vagg et al. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
- Mastering the game of Go with deep neural networks and tree search
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- Data-Driven Reinforcement Learning–Based Real-Time Energy Management System for Plug-In Hybrid Electric Vehicles
- (2016) Xuewei Qi et al. TRANSPORTATION RESEARCH RECORD
- An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning
- (2015) Yue Hu et al. Energies
- Reinforcement Learning–Based Energy Management Strategy for a Hybrid Electric Tracked Vehicle
- (2015) Teng Liu et al. Energies
- An energy management approach of hybrid vehicles using traffic preview information for energy saving
- (2015) Chunhua Zheng et al. ENERGY CONVERSION AND MANAGEMENT
- Fuzzy-based blended control for the energy management of a parallel plug-in hybrid electric vehicle
- (2015) Nicolas Denis et al. IET Intelligent Transport Systems
- Human-level control through deep reinforcement learning
- (2015) Volodymyr Mnih et al. NATURE
- An instantaneous optimization strategy based on efficiency maps for internal combustion engine/battery hybrid vehicles
- (2014) Kürşad Gökce et al. ENERGY CONVERSION AND MANAGEMENT
- Power management optimization of fuel cell/battery hybrid vehicles with experimental validation
- (2013) Farouk Odeim et al. JOURNAL OF POWER SOURCES
- Optimal energy management in a dual-storage fuel-cell hybrid vehicle using multi-dimensional dynamic programming
- (2013) Mehdi Ansarey et al. JOURNAL OF POWER SOURCES
- Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming
- (2013) Zheng Chen et al. JOURNAL OF POWER SOURCES
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- (2012) Weimin Li et al. Chinese Journal of Mechanical Engineering
- Classification and Review of Control Strategies for Plug-In Hybrid Electric Vehicles
- (2010) Sanjaka G. Wirasingha et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Optimal fuzzy power control and management of fuel cell/battery hybrid vehicles
- (2009) Chun-Yan Li et al. JOURNAL OF POWER SOURCES
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