Abstract
To improve the working performance of battery electric vehicle (BEV) high-speed helical gear transmission under full working conditions, combined with Tooth Contact Analysis (TCA) and Loaded Tooth Contact Analysis (LTCA), the vibration model of single-stage helical gear bending-torsion-axis-swing coupling system considering time-varying mesh stiffness was established. The genetic algorithm was used to optimize the tooth surface with the objective of minimizing the mean value of the vibration acceleration at full working conditions. Finally, a high-speed helical gear transmission system in a BEV gearbox was taken as a simulation example and the best-modified tooth surface at full working conditions was obtained. Experiment and simulation results show that the proposed calculation method of time-varying meshing stiffness is accurate, and tooth surface modification can effectively suppress the vibration of high-speed helical gear transmission in BEV; compared to the optimally modified tooth surface under a single load, the optimal modified tooth surface under full working conditions has a better vibration reduction effect over the entire working range.
Highlights
With the aggravation of energy and environmental issues, the new energy vehicles have achieved rapid development
To pursue the power density ratio, EVs often use high-speed motors, resulting in the input speed of the gear reducer directly connected to the motor being too high, which unavoidably presents a significant challenge to the dynamic performance of the gear transmission in the battery electric vehicle (BEV) gearbox, which has a significant effect on the vehicle’s reliability, stability, and vibration noise
Tooth surface modification is an important means of vibration suppression and noise reduction of gear transmission
Summary
With the aggravation of energy and environmental issues, the new energy vehicles have achieved rapid development. Tooth surface modification is an important means of vibration suppression and noise reduction of gear transmission. In Bonori’s work [4], an optimization approach based on genetic algorithms was proposed to improve gear dynamic performance with a view to noise reduction; linear and parabolic profile modifications were considered and compared by means of several optimization strategies based on static nonlinear FEM analysis. Wang [9,10] studied the vibration reduction effect of 3D modification on helical gears; in his work, a multi-objective modification optimal design method for helical gear considering an evenly distributed load on the tooth surface and vibration and noise reduction was proposed. Liu [14] et al developed a nonlinear analytical model; the effect of tooth profile modification on the vibration of the multi-meshing gear group was investigated. Where m is the equivalent torsional mass of the gear pair, which is expressed as me
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