4.6 Article

Supervisory control of the hybrid off-highway vehicle for fuel economy improvement using predictive double Q-learning with backup models

Related references

Note: Only part of the references are listed.
Article Energy & Fuels

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Quan Zhou et al.

Summary: In order to reduce the workload of developing the energy management controller for electric vehicles, this paper studies an innovative transfer learning routine. A new transferable representation control model is proposed by incorporating two promising artificial intelligence technologies, resulting in competitive real-time control utility values achieved through experimental evaluations.

APPLIED ENERGY (2022)

Article Energy & Fuels

Double deepQ-learningcoordinated control of hybrid energy storage system in island micro-grid

Yunjun Yu et al.

Summary: This study focuses on using a hybrid energy storage system in island micro-grids to address energy demands, proposing the Double deep Q-learning algorithm for optimizing control strategies. Experimental results demonstrate the method's effectiveness in handling various weather conditions and increasing renewable energy utilization.

INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2021)

Article Energy & Fuels

A Double-Deep Q-Network-Based Energy Management Strategy for Hybrid Electric Vehicles under Variable Driving Cycles

Jiaqi Zhang et al.

Summary: This study proposes a double-deep Q-network (DDQN)-based energy management strategy (EMS) for hybrid electric vehicles (HEVs) under variable driving cycles. By introducing the distance traveled as states and utilizing deep neural network for good generalization, the curse of dimensionality problem is solved, and two different neural networks are designed to address the overestimation issue in model training.

ENERGY TECHNOLOGY (2021)

Article Computer Science, Artificial Intelligence

Knowledge Implementation and Transfer With an Adaptive Learning Network for Real-Time Power Management of the Plug-in Hybrid Vehicle

Quan Zhou et al.

Summary: The paper introduces a new adaptive learning network that combines DDPG and ANFIS networks for energy management in plug-in hybrid vehicles, showing superior performance in real-world driving conditions.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Construction & Building Technology

Robotic assembly of timber joints using reinforcement learning

Aleksandra Anna Apolinarska et al.

Summary: This paper introduces the application of Reinforcement Learning in controlling robot movements for assembly tasks in architectural construction, with a successful demonstration in timber structure assembly. The control policy is trained in simulation to address uncertainties in reality and customization requirements for differentiated designs.

AUTOMATION IN CONSTRUCTION (2021)

Article Automation & Control Systems

Global Optimization of he Hydraulic-Electromagnetic Energy-Harvesting Shock Absorber for Road Vehicles With Human-Knowledge-Integrated Particle Swarm Optimization Scheme

Quan Zhou et al.

Summary: This study proposes a human-knowledge-integrated particle swarm optimization scheme for optimizing the design of hydraulic-electromagnetic energy-harvesting shock absorbers for road vehicles. Experimental results show that the scheme achieved the optimal energy recovery efficiency under global conditions.

IEEE-ASME TRANSACTIONS ON MECHATRONICS (2021)

Review Green & Sustainable Science & Technology

Electric vehicles and charging infrastructure in Turkey: An overview

Omer Gonul et al.

Summary: This study focuses on Turkey's position in electric vehicle technology, evaluating the current state of EV, charging infrastructure, battery market, regulations, R&D activities, and industry. Recommendations are made to address deficiencies in charging infrastructure, raise awareness in society, and strengthen EVCS infrastructure in the eastern part of the country.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

Article Engineering, Electrical & Electronic

Modified Particle Swarm Optimization With Chaotic Attraction Strategy for Modular Design of Hybrid Powertrains

Quan Zhou et al.

Summary: This article proposes a new modular design method for hybrid powertrains using a modified accelerated particle swarm optimization (MAPSO) algorithm. The method determines the optimal combination of component specifications and control parameters, and a Pareto analysis is carried out for tradeoff determination. The MAPSO is verified as the best method and two different modular design methods are developed with it, with the simultaneous method showing better performance in terms of cost function and time savings compared to the two-level method.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2021)

Review Engineering, Electrical & Electronic

A Review of Range Extenders in Battery Electric Vehicles: Current Progress and Future Perspectives

Manh-Kien Tran et al.

Summary: Emissions from the transportation sector have a significant impact on climate change and health issues, and range anxiety is a major limitation to the adoption of electric vehicles. Range extending technologies, such as internal combustion engines and fuel cells, offer solutions to extend the driving range of EVs and address consumer concerns.

WORLD ELECTRIC VEHICLE JOURNAL (2021)

Article Transportation Science & Technology

An ensemble deep learning approach for driver lane change intention inference

Yang Xing et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)

Proceedings Paper Engineering, Electrical & Electronic

Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition

Teng Liu et al.

2020 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC) (2020)

Article Automation & Control Systems

Cyber-Physical Energy-Saving Control for Hybrid Aircraft-Towing Tractor Based on Online Swarm Intelligent Programming

Quan Zhou et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)

Article Engineering, Electrical & Electronic

Convex Optimization Methods for Powertrain Sizing of Electrified Vehicles by Using Different Levels of Modeling Details

Mitra Pourabdollah et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)

Article Engineering, Electrical & Electronic

Learning Driver-Specific Behavior for Overtaking: A Combined Learning Framework

Chao Lu et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)

Article Automation & Control Systems

Reinforcement Learning of Adaptive Energy Management With Transition Probability for a Hybrid Electric Tracked Vehicle

Teng Liu et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)

Article Computer Science, Interdisciplinary Applications

Optimization of power management in an hybrid electric vehicle using dynamic programming

Laura V. Perez et al.

MATHEMATICS AND COMPUTERS IN SIMULATION (2006)