Journal of South China University of Technology (Natural Science Edition) ›› 2016, Vol. 44 ›› Issue (3): 68-75.doi: 10.3969/j.issn.1000-565X.2016.03.010

• Automotive Engineering • Previous Articles     Next Articles

Parameter Optimization of Powertrain System for Electric Vehicles Oriented to Performance Requirements

XIONG Hui-yuan1,2 WU Xiao-li1 ZONG Zhi-jian1,2 YU Li-min1   

  1. 1.School of Engineering,Sun Yat-Sen University,Guangzhou 510006,Guangdong,China; 2.Institute of Dongguan-Sun Yat-Sen University,Dongguan 523808,,Guangdong,China
  • Received:2015-02-12 Revised:2015-05-19 Online:2016-03-25 Published:2016-02-02
  • Contact: 熊会元(1973-)，男，博士，副教授，主要从事电动汽车集成设计优化技术研究． E-mail:xionghy@mail.sysu.edu.cn
  • About author:熊会元(1973-)，男，博士，副教授，主要从事电动汽车集成设计优化技术研究．
  • Supported by:
    Supported by the Key Technology Research Project of Strategic Emerging Industry in Guangdong Province (2012A010702001)

PDF

246

Abstract: Proposed in this paper is an integrated design and optimization method of powertrain parameters for elec- tric vehicles on the basis of QFD (Quality Function Deployment) and orthogonal test,which promotes the compre- hensive performance of electric vehicles effectively.Firstly,a QFD-based coupling model considering both customer requirements and technical characteristics is set up,and the weighting factors of technical characteristics are deter- mined by applying rough number and grey correlation method.Secondly,an optimization model of powertrain pa- rameters is constructed through orthogonal test,with vehicle comprehensive performance being taken as the objec- tive.Then,the comprehensive performance coefficients of vehicles are obtained by means of grey correlation method,and the optimal solution to multi-objective optimization as well as the sensibility analysis of performance factors is dealt with.Finally,a design and optimization model on Matlab platform is established and is further verified with an electric vehicle.An increment of 32.3% in comprehensive performance is obtained,which verifies the effective- ness of the proposed method.

Key words: electric vehicle, quality function deployment, orthogonal test, sensibility analysis, grey correlation method

CLC Number: