Computationally Efficient Energy Management for a Parallel Hybrid Electric Vehicle Using Adaptive Dynamic Programming
Author:
Affiliation:
1. Department of Engineering Design, KTH Royal Institute of Technology, Brinellvägen 83, Stockholm, Sweden
2. Department of Electrical Engineering, KTH Royal Institute of Technology, Electrum 229, Kista, Sweden
Funder
China Scholarship Council (CSC), KTH Excellence in Production Research (XPRES), and Trustworthy Edge Computing Systems and Applications
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Control and Optimization,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/7274857/7448921/10149522.pdf?arnumber=10149522
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4. Numerical Analysis of Optimal Hybridization in Parallel Hybrid Electric Powertrains for Tracked Vehicles;Energies;2024-07-18
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