Title :
A study of engine fuel economy and its optimization method in hybrid electric vehicles based on MATLAB toolbox
Author :
Deng, Yuanwang ; Zhou, Fei ; Zhang, Bangji ; Jia, GuoHai ; Chen, Keliang
Author_Institution :
Coll. of Mech. & Vehicle Eng., Hunan Univ., Changsha, China
Abstract :
Neural network and numerical analysis methods are studied, and applied to create the models of fuel economy for CFA6470 parallel hybrid electric vehicle (CFA6470PHEV) engine. Based on optimally designing configuration and parameters of the models, the optimal models of fuel economy are achieved. With numerical analysis methods, the engine cycles having optimal fuel economy has been determined, along with the relationship of throttle angle and fuel economy of the engine determined too. The optimal fuel economy of the engine can be controlled with adjusting the throttle angle.
Keywords :
engines; fuel economy; hybrid electric vehicles; mechanical engineering computing; neural nets; numerical analysis; optimisation; CFA6470 parallel hybrid electric vehicle engine; MATLAB toolbox; engine cycles; engine fuel economy; neural network; numerical analysis methods; optimization method; throttle angle; Artificial neural networks; Biological system modeling; Engines; Fuel economy; Torque; Vehicles; engine; fuel economy; hybrid electric vehicles (HEVs); neural network; numerical analysis;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5776938
