DocumentCode :
3164829
Title :
Statistic Driving Cycle Analysis and application for hybrid electric vehicle parametric design
Author :
Tan, Di ; Luo, Yutao ; Huang, Xiangdong
Author_Institution :
Sch. of Mech.&Auto Eng., South China Univ. of Technol., Guangzhou, China
fYear :
2011
fDate :
16-18 April 2011
Firstpage :
5259
Lastpage :
5263
Abstract :
An optimal parametric design is the precondition of an excellent performance of a HEV. A novel approach, Statistic Driving Cycles Analysis (SDCA), is put forward. The SDCA is based on the characteristic statistic of the existing driving cycles. In order to analyze the driving cycles commendably, a novel concept, Cycle Block, is put forward correspondingly. By choosing the characteristic parameters to represent the driving cycles, most of the typical driving cycles are statistically analyzed. As a consequence, taking a midsize HEV designing as an example, the optimal parameters are calculated. To evaluate the feasibility of the SDCA method, some simulations are carried out. A stochastic made up driving cycle is used to evaluate the adaptitude of the SDCA method. Further more, the contrastive simulations are carried out to test the advantage of the SDCA method.
Keywords :
hybrid electric vehicles; statistical analysis; HEV parametric design; SDCA method; hybrid electric vehicle parametric design; statistic driving cycle analysis; Acceleration; Electric motors; Engines; Fuels; Hybrid electric vehicles; Optimization; Cycle block; Driving cycle; Hybrid electric vehicle; Parametric matching; Statistic analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
Type :
conf
DOI :
10.1109/CECNET.2011.5769094
Filename :
5769094
Link To Document :
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