[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Li et al., 2023 - Google Patents

Data-driven bi-level predictive energy management strategy for fuel cell buses with algorithmics fusion

Li et al., 2023

View HTML
Document ID
9927963165109752909
Author
Li M
Liu H
Yan M
Wu J
Jin L
He H
Publication year
Publication venue
Energy Conversion and Management: X

External Links

Snippet

This paper aims to answer how to effectively integrate the data-driven method into the traditional predictive energy management algorithm rather than replacing it outright. Given the challenge of selecting an appropriate prediction horizon for predictive energy …
Continue reading at www.sciencedirect.com (HTML) (other versions)

Classifications

    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage for electromobility
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies related to electric vehicle charging
    • Y02T90/12—Electric charging stations
    • Y02T90/128—Energy exchange control or determination
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies related to electric vehicle charging
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce green house gasses emissions common to all road transportation technologies
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Lei et al. An adaptive equivalent consumption minimization strategy for plug-in hybrid electric vehicles based on traffic information
Lü et al. Hybrid electric vehicles: A review of energy management strategies based on model predictive control
Zhou et al. A novel energy management strategy of hybrid electric vehicle via an improved TD3 deep reinforcement learning
Lian et al. Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle
Huang et al. Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm
Li et al. Adaptive energy management strategy for fuel cell/battery hybrid vehicles using Pontryagin's Minimal Principle
Yuan et al. Intelligent energy management strategy based on hierarchical approximate global optimization for plug-in fuel cell hybrid electric vehicles
Du et al. Energy management for a hybrid electric vehicle based on prioritized deep reinforcement learning framework
Yang et al. A reinforcement learning-based energy management strategy for fuel cell hybrid vehicle considering real-time velocity prediction
Xu et al. Optimization of energy management strategy for extended range electric vehicles using multi-island genetic algorithm
Jia et al. Learning-based model predictive energy management for fuel cell hybrid electric bus with health-aware control
Qi et al. Generalization ability of hybrid electric vehicle energy management strategy based on reinforcement learning method
Guo et al. Cost-optimal energy management strategy for plug-in hybrid electric vehicles with variable horizon speed prediction and adaptive state-of-charge reference
Mei et al. A deep reinforcement learning approach to energy management control with connected information for hybrid electric vehicles
Sun et al. A real-time PMP energy management strategy for fuel cell hybrid buses based on driving segment feature recognition
Fang et al. Online power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning and driving cycle reconstruction
Zhang et al. Hierarchical reinforcement learning based energy management strategy of plug-in hybrid electric vehicle for ecological car-following process
Li et al. Data-driven bi-level predictive energy management strategy for fuel cell buses with algorithmics fusion
Guo et al. Research on energy management strategy of heavy-duty fuel cell hybrid vehicles based on dueling-double-deep Q-network
Li et al. Incentive learning-based energy management for hybrid energy storage system in electric vehicles
Hu et al. Performance analysis of AI-based energy management in electric vehicles: A case study on classic reinforcement learning
Kong et al. A data-driven energy management method for parallel PHEVs based on action dependent heuristic dynamic programming (ADHDP) model
He et al. Energy management optimization for connected hybrid electric vehicle using offline reinforcement learning
Pan et al. Grey wolf fuzzy optimal energy management for electric vehicles based on driving condition prediction
Viji et al. Hybrid STO-IWGAN method based energy optimization in fuel cell electric vehicles