Energy management strategy for HEV based on KFCM and neural network
Author:
Affiliation:
1. Faculty of AutomationHuaiyin Institute of Technology Huaian China
2. School of Mechanical EngineeringSoutheast University Nanjing China
3. College of Electrical Engineering and Control ScienceNanjing Tech University Nanjing China
Funder
National Natural Science Foundation of China
Six Talent Peaks Project in Jiangsu Province
Publisher
Wiley
Subject
Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.4838
Reference13 articles.
1. Survey on energy management strategies for hybrid electric vehicles;Zhao XC;Acta Autom Sin,2016
2. Real‐time optimization control algorithm of energy management strategy for hybrid electric vehicles;Xia CY;Acta Autom Sin,2015
3. Research status of hybrid electric vehicle energy management strategy based on the driving cycle;Lin X;J Hebei Univ Sci Technol,2016
4. Power Smoothing Energy Management and Its Application to a Series Hybrid Powertrain
5. A Novel ECMS and Combined Cost Map Approach for High-Efficiency Series Hybrid Electric Vehicles
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