TY - JOUR
T1 - Study on the Evaluation Model of Vehicle Comfort Based on the Neural Network
AU - Huang, Fengnan
AU - Zhao, Changlu
AU - Huang, Ying
AU - Dai, Peilin
AU - Hao, Donghao
AU - Yue, Yunpeng
N1 - Publisher Copyright:
© 2018
PY - 2018
Y1 - 2018
N2 - Due to the subjective perception of the driver, the comfort cannot be described by the objective indexes, meanwhile the normal subjective evaluation methods require plenty of human and material resources. Therefore, in this paper, in order to evaluate the comfort when the vehicle occurs low frequency longitudinal vibration during Tipin/out operations, a comfort evaluation method based on the neural network model is developed. First of all, through the mechanism analysis of the low frequency longitudinal vibration, three basic signals of the objective evaluation are determined. During different Tipin/out operations, the basic signals are collected by the experiment instruments and the subjective evaluation grades are determined by professionals. After that, the basic signals are weighted filtered and transformed into three objective evaluation indexes. Finally, the neural network model is trained by a large number of subjective evaluation grades and the objective evaluation indexes. The comfort performance of the vehicle during Tipin/out operations can be evaluated by the evaluation method.
AB - Due to the subjective perception of the driver, the comfort cannot be described by the objective indexes, meanwhile the normal subjective evaluation methods require plenty of human and material resources. Therefore, in this paper, in order to evaluate the comfort when the vehicle occurs low frequency longitudinal vibration during Tipin/out operations, a comfort evaluation method based on the neural network model is developed. First of all, through the mechanism analysis of the low frequency longitudinal vibration, three basic signals of the objective evaluation are determined. During different Tipin/out operations, the basic signals are collected by the experiment instruments and the subjective evaluation grades are determined by professionals. After that, the basic signals are weighted filtered and transformed into three objective evaluation indexes. Finally, the neural network model is trained by a large number of subjective evaluation grades and the objective evaluation indexes. The comfort performance of the vehicle during Tipin/out operations can be evaluated by the evaluation method.
KW - comfort evaluation
KW - low frequency longitudinal vibration
KW - objective evaluation index
KW - subjective evaluation grade
KW - the neural network model
UR - https://www.scopus.com/pages/publications/85056186886
U2 - 10.1016/j.ifacol.2018.10.125
DO - 10.1016/j.ifacol.2018.10.125
M3 - 会议文章
AN - SCOPUS:85056186886
SN - 2405-8971
VL - 51
SP - 553
EP - 558
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
IS - 31
T2 - 5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2018
Y2 - 20 September 2018 through 22 September 2018
ER -