DocumentCode :
2906224
Title :
Intelligent Energy Management Based on Driving Cycle Identification Using Fuzzy Neural Network
Author :
Yi, Tian ; Xin, Zhang ; Liang, Zhang ; Xinn, Zhang
Author_Institution :
Sch. of Mech. Electr. & Control Eng., Beijing Jiaotong Univ., Beijing, China
Volume :
2
fYear :
2009
fDate :
12-14 Dec. 2009
Firstpage :
501
Lastpage :
504
Abstract :
Hybrid electric vehicles (HEV) is becoming the important develop tendency of the vehicle for its better fuel economy and emission. The parameters of HEV control strategy is always optimized on some one standardized driving cycle, but the different city have its own driving cycle. So the great advantage of HEV is limited. This paper proposes an intelligent management for parallel HEV based on driving cycle identification using fuzzy neural network. Fuzzy neural network is great in model identification. The intelligent energy management of HEV identifies the driving cycle and changes the parameters of the control strategy. The applicability of the proposed intelligent control system is confirmed by simulation examples. The simulation results show that the control strategy based on driving cycle identification using fuzzy neural network could further improve the fuel consumption and reduce emissions.
Keywords :
energy management systems; fuel economy; fuzzy control; fuzzy neural nets; hybrid electric vehicles; neurocontrollers; driving cycle identification; fuel economy; fuel emission; fuzzy neural network; hybrid electric vehicle control strategy; intelligent control system; intelligent energy management; parallel hybrid electric vehicle; Battery powered vehicles; Competitive intelligence; Energy management; Engines; Fuzzy control; Fuzzy neural networks; Hybrid electric vehicles; Intelligent networks; Torque; Vehicle driving; control strategy; driving cycle; fuzzy neural network; genetic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
Type :
conf
DOI :
10.1109/ISCID.2009.271
Filename :
5368792
Link To Document :
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