Volume 21 Issue 2
Aug.  2021
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WU Sheng-li, XING Wen-ting, SHAO Yi-ming, JIAN Xiao-chun, ZHAO Shu-en. Analysis of factors affecting vehicle driving condition based on road test in Chongqing[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 150-158. doi: 10.19818/j.cnki.1671-1637.2021.02.013
Citation: WU Sheng-li, XING Wen-ting, SHAO Yi-ming, JIAN Xiao-chun, ZHAO Shu-en. Analysis of factors affecting vehicle driving condition based on road test in Chongqing[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 150-158. doi: 10.19818/j.cnki.1671-1637.2021.02.013
shu

Analysis of factors affecting vehicle driving condition based on road test in Chongqing

doi: 10.19818/j.cnki.1671-1637.2021.02.013
  • 1.

    School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China

  • 2.

    School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing 400067, China

  • 3.

    School of Mechanotronics and Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China

Funds:  National Key Research and Development Program of China (2016YFB0100905-4); National Natural Science Foundation of China (51705052); Natural Science Foundation of Chongqing (cstc2019jcyj-msxmX0779)
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  • Author Bio:

    WU Sheng-li(1983-), male, associate professor, PhD, wushengli20008@163.com

  • Corresponding author: SHAO Yi-ming(1955-), male, professor, PhD, sym@cqjtu.edu.cn
  • Received Date: 2020-11-03
  • Publish Date: 2021-04-01
    Abstract
  • The vehicle road test method was used, and the vehicle driving status data were collected through the VBOX, an exhaust gas collection system, and a gyroscope. Based on the method of projection pursuit dynamic clustering, combined with the NSGA-Ⅱ method with an elite control strategy, different parameter indexes were processed, and the influence degrees of parameters on automotive fuel economy and emission characteristics were quantitatively analyzed. The change rules of influencing characteristics of different parameters under specific working conditions were studied. Research result shows that in all driving conditions, the weight of the impact of acceleration on the fuel economy is 65.52%, the weight of the impact on the VSP characteristic is 35.03%, and the impact weight of the turning radius on the VSP characteristic is 37.86%. When the vehicle speed is less than 10 km·h-1, the turning radius has the greatest impact on the fuel economy, and its impact weight is 80.74%. The acceleration has the greatest impact on the VSP characteristic, and its impact weight is 82.82%. When the vehicle speed is 10-40 km·h-1, the acceleration has the greatest impact on the fuel economy and VSP characteristic, and its impact weights are 34.01% and 48.59%, respectively. When the vehicle speed is greater than 40 km·h-1, the slope has the greatest impact on the fuel economy, and its impact weight is 75.59%. Vehicle speed has the greatest impact on the VSP characteristic, with an impact weight of 80.17%. When the vehicle is in a downhill condition, the weight of the slope's impact on the fuel economy is 69.84%, and the weight of the speed's impact on the VSP characteristic is 56.37%. When the vehicle is in an uphill condition, the impact weights of acceleration on the fuel economy and VSP characteristic are 54.62% and 94.24%, respectively. A quantitative analysis of the impact weights of different factors on fuel economy and VSP characteristic not only provides practical support for improving them, but also provides an important theoretical basis for intelligent vehicle control algorithms. 11 figs, 31 refs.

     

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