DocumentCode :
231811
Title :
Fuzzy energy management strategy for plug-in hev based on driving cycle modeling
Author :
Wu Jian
Author_Institution :
Dept. of Inf. Sci. & Technol., Shandong Univ. of Political Sci. & Law, Jinan, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
4472
Lastpage :
4476
Abstract :
The fuzzy energy management strategy for a plug-in hybrid electric vehicle (PHEV) is proposed by modeling of driving cycle and optimization of fuzzy controller. Firstly, the driving cycle model is constructed with BP neural network based on the driving data of Shandong university school bus. Then the membership functions and rules of fuzzy torque distribution controller are optimized by using particle swarm optimization in accordance with the driving cycle model. The test results from the ADVISOR platform show that compared with the un-optimized strategies, the fuzzy energy management strategy based on the driving cycle modeling can lower the cost of driving effectively.
Keywords :
backpropagation; fuzzy control; hybrid electric vehicles; neurocontrollers; particle swarm optimisation; road vehicles; torque control; ADVISOR platform; BP neural network; Shandong university school bus; backpropagation; driving cycle modeling; fuzzy controller optimization; fuzzy energy management strategy; fuzzy torque distribution controller; membership functions; particle swarm optimization; plug-in HEV; plug-in hybrid electric vehicle; Educational institutions; Energy management; Engines; Optimization; System-on-chip; Torque; Vehicles; Fuzzy energy management strategy; Plug-in hybrid electric vehicle; driving cycle modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6895690
Filename :
6895690
Link To Document :
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