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Dynamic Meshing Force Analysis of Parallel Planetary Gear based on RBF Neural Network

Authors :
Xia Yuan
Xiaohua Hao
Xuewen Song
Jianli Zhang
Gang An
Source :
Jixie chuandong, Vol 45, Pp 140-146 (2021)
Publication Year :
2021
Publisher :
Editorial Office of Journal of Mechanical Transmission, 2021.

Abstract

The double motor hybrid vehicle distributes the power on both sides through the parallel planetary gear mechanism. The meshing force of the two rows of planetary gears affects each other, resulting in the increase of dynamic load coefficient and vibration excitation. The harmonic analysis method is used to obtain the frequency ratio of meshing force under multiple working conditions, so as to establish RBF neural network model, and a prediction of meshing force in a certain working range is carried out. The maximum meshing force and dynamic load coefficient are calculated on the prediction results, and the meshing force is proportional to the difference between speed ratio and output torque ratio minus 1, and the dynamic load coefficient on the low-speed side is greater than that on the high-speed side, which can be expressed as a multiple or reciprocal multiple relationship. It provides a theoretical basis for the study of dynamics of hybrid vehicles with dual motors.

Details

Language :
Chinese
ISSN :
10042539
Volume :
45
Database :
Directory of Open Access Journals
Journal :
Jixie chuandong
Publication Type :
Academic Journal
Accession number :
edsdoj.85ff0bc6f2644cab6ce489b95e8a5e5
Document Type :
article
Full Text :
https://doi.org/10.16578/j.issn.1004.2539.2021.03.023