Real-Time Energy Management Strategy of a Fuel Cell Electric Vehicle With Global Optimal Learning-Reference-Cited by-同舟云学术

Real-Time Energy Management Strategy of a Fuel Cell Electric Vehicle With Global Optimal Learning

Published:2023-12 Issue:4 Volume:9 Page:5085-5097
ISSN:2332-7782
Container-title:IEEE Transactions on Transportation Electrification
language:
Short-container-title:IEEE Trans. Transp. Electrific.

Author:

Hou Shengyan¹^ORCID,Yin Hai²,Pla Benjamín³^ORCID,Gao Jinwu¹^ORCID,Chen Hong⁴^ORCID

Affiliation:

1. State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering, Jilin University, Changchun, China

2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, China

3. CMT-Motores Térmicos, Universitat Politècnica de València, Valencia, Spain

4. Department of Control Science and Engineering, Jilin University, Changchun, China

Funder

National Natural Science Foundation of China

Technology Development Program of Jilin Province

China Automobile Industry Innovation and Development Joint Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Transportation,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6687316/10364905/10021673.pdf?arnumber=10021673

Reference54 articles.

1. A scalable, causal, adaptive energy management strategy based on optimal control theory for a fuel cell hybrid railway vehicle

2. Total travel costs minimization strategy of a dual-stack fuel cell logistics truck enhanced with artificial potential field and deep reinforcement learning

3. Convex programming energy management and components sizing of a plug-in fuel cell urban logistics vehicle

4. Chance-constrained robust co-design optimization for fuel cell hybrid electric trucks

5. Joint Component Sizing and Energy Management for Fuel Cell Hybrid Electric Trucks

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