Integrating Model Predictive Control With Federated Reinforcement Learning for Decentralized Energy Management of Fuel Cell Vehicles
Author:
Affiliation:
1. Department of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China
2. Hydrogen Research Institute, Department of Electrical and Computer Engineering, Université du Québec à Trois-Rivières, Trois-Rivières, Canada
Funder
Natural Sciences and Engineering Research Council of Canada
Canada Research Chairs Program
Talent Plan Project of Chongqing
National Key Research and Development Program
Project of Basic Research Funds for Central Universities
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10339106/10227745.pdf?arnumber=10227745
Reference73 articles.
1. Predictive Control of Voltage and Current in a Fuel Cell–Ultracapacitor Hybrid
2. A review of the gas diffusion layer in proton exchange membrane fuel cells: Durability and degradation
3. A Power Allocation Method for Multistack PEMFC System Considering Fuel Cell Performance Consistency
4. Degradation mechanisms of proton exchange membrane fuel cell under typical automotive operating conditions
5. Energy management of fuel cell/battery/supercapacitor hybrid power sources using model predictive control;bambang;IEEE Trans Ind Informat,2014
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