2nd International Conference On Systems Engineering and Modeling (ICSEM-13)

Matching and Optimization for Powertrain System of Parallel Hybrid Electric Vehicle

Authors
Jianping Gao, Yuehui Wei, Zhennan Liu, Hongbing Qiao
Corresponding Author
Jianping Gao
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.61How to use a DOI?
Keywords
hybrid electric vehicle, driving cycle analysis, powertrain system matching, combinatorial optimization algorithm
Abstract
The parameters matching of the hybrid powertrain system of the hybrid electric vehicle has a directly impact on the performance of the vehicle dynamic and the fuel economy. The preliminary match of the powertrain system base on analysis of Driving Cycle is done, then the software of AVL-Cruise and Matlab are integrated with Isight to optimize parameters of match, by using the Multi-Island GA and NLPQL to establish the combinatorial optimization algorithm. The results show that the fuel economy have been improved by 10.92% without sacrificing the dynamic performance and under the premise of ensuring the limits of the state of charge of battery.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-94-91216-42-8
DOI
https://doi.org/10.2991/icsem.2013.61How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jianping Gao
AU  - Yuehui Wei
AU  - Zhennan Liu
AU  - Hongbing Qiao
PY  - 2013/04
DA  - 2013/04
TI  - Matching and Optimization for Powertrain System of Parallel Hybrid Electric Vehicle
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/icsem.2013.61
DO  - https://doi.org/10.2991/icsem.2013.61
ID  - Gao2013/04
ER  -