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
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