Abstract
The NVH (Noise, Vibration, and Harshness) characteristics of new energy vehicles are the key indexes to measure interior comfort. The multi-stage gear reducer in the transmission system is the primary source of vibration and noise. The parameterized 3D model of the multi-stage gear transmission system of the new energy vehicle was established through Romax software, and the comprehensive gear modification method of the tooth direction combined with the tooth profile was built. Then a complete simulation analysis process is established to solve the maximum vibration acceleration of the multi-stage gear transmission system under constant speed condition, to obtain the simulation data of two-stage gear set under different modification parameters. The traditional BP (Back Propagation) neural network is optimized and improved through the optimal selection of network parameters combined with Bayesian regularization. Based on the optimized BP neural network, a modified parameter-vibration noise prediction model is constructed. Finally, the GA (Genetic Algorithm) optimization algorithm is used to solve the prediction model to obtain the optimal combination of modification parameters aiming at the minimum vibration acceleration, the effectiveness and reliability of the modified design are verified through actual simulation. It provides ideas and a basis for the research on vibration and noise reduction of multi-stage gears.
Highlights
In the running process of new energy vehicles, the vibration of the gear transmission system caused by alternate meshing will reduce the service life of gears, and the vibration noise will have a great impact on the vehicle experience
The results show that the transmission error of the gear is reduced and the load distribution on the tooth surface is uniform
With vibration reduction and noise reduction as the direct optimization goal, the GA optimization algorithm is used to solve the prediction model to obtain the optimal combination of modification parameters, the effectiveness and reliability of the modification design are verified through actual simulation
Summary
In the running process of new energy vehicles, the vibration of the gear transmission system caused by alternate meshing will reduce the service life of gears, and the vibration noise will have a great impact on the vehicle experience. Xu et al [9] established the tooth profile modification model of the planetary gear system and analyzed the influence of modification parameters on the time-varying meshing stiffness and transmission error of the planetary gear system. Xu et al [20] proposed a method that combines tooth shape, tooth orientation modification, and the dual objective function to establish an optimization model to reduce the noise of gear reducer of electric vehicles. Through the parametric 3D modeling of a multistage gear transmission system of new energy vehicles by Romax software, the comprehensive modification method of tooth alignment and tooth profile is determined. With vibration reduction and noise reduction as the direct optimization goal, the GA optimization algorithm is used to solve the prediction model to obtain the optimal combination of modification parameters, the effectiveness and reliability of the modification design are verified through actual simulation.
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