With increasingly stringent global emission regulations, new energy vehicles have become the focus of attention for major car manufacturers worldwide. Compared to traditional fuel vehicles, pure electric vehicles have better economy and environmental friendliness. However, due to the lack of the shielding effect of the engine on noise, the wind noise, tire noise, and mechanical noise of pure electric vehicles are prominent, with the most severe being gearbox noise, which is generally distributed in the frequency range of 700-4000Hz. The human ear is very sensitive to noise within this range, and its high-frequency noise can seriously affect the comfort of drivers and passengers. Especially in recent years, pure electric vehicle reducers have been continuously developing towards higher speeds, pushing high-frequency noise issues to their peak. The high-frequency noise generated by the gearbox of pure electric vehicles is mainly due to the rigid flexible coupling response generated by the gearbox under dynamic excitation, which is caused by the transmission error generated during the meshing process of the carrying helical gear, and is a type of noise generated through frequency tuning. Transmission error is the deviation between the actual meshing and theoretical meshing of helical gears, which generates excitation force and causes vibration. It is transmitted through supporting bearings and the casing, radiating noise. Transmission error is the fundamental cause of helical gear whistling noise. There are various ways to optimize the transmission error of reducers, such as optimizing the coincidence degree of helical gears at a macro level; Optimize the tooth profile of helical gears at the micro level; Or improve installation accuracy during assembly, etc. The most economical, efficient, and effective way is to optimize the micro helical gear tooth profile. By performing micro modification on helical gears, the load distribution of helical gears can be significantly improved, and the internal excitation of helical gears, such as meshing excitation and error excitation, can be reduced, thereby optimizing the whistling noise of helical gears.
At present, simulation and calculation methods are commonly used to optimize the transmission error and tooth contact stress of helical gears. Its advantages lie in saving time, manpower, and material resources, high efficiency, and good economy and applicability. Bai Guoqing and others conducted a study on the modification and optimization of helical gears with fine and high teeth through simulation. The research results showed that the modification of helical gears can reduce transmission errors and make the transmission more stable. Tan Wei and his team used genetic algorithm to perform micro tooth surface modification design on the noise source helical gear pair of hybrid electric transmissions, and obtained the optimal combination of helical gear modification. The feasibility of the modification scheme was verified through simulation experiments. Sun Jianguo and others established finite element models of standard involute helical gears and modified helical gears through simulation, and analyzed their dynamic contact. The results showed that suitable modification of helical gears can significantly improve the impact condition of helical gears. Zhou Xinjian and others used Romax software to simulate and compare two modification schemes for the second gear helical gear of a dual clutch transmission, and obtained the optimal modification scheme, which improved the transmission error of the helical gear. They conducted experimental verification, and the results showed that the optimal modification scheme significantly optimized the NVH performance of the vehicle.
As a micro level structural design method, the micro modification accuracy of helical gears is not only affected by subjective modification amount, but also by simulation calculation accuracy. As one of the most important parameters in simulation calculations, the number of grids and their partitioning methods affect the time and accuracy of simulation calculations. In theory, the accuracy of simulation solutions increases with the increase of the number of grids. However, in reality, having too many or too few grids can affect the accuracy of simulation calculations. At present, there is very little literature on methods for verifying the accuracy of simulation calculations. The verification of simulation results mostly relies on experimental verification, and there has not been in-depth exploration and research on the number of simulation calculation grids and their partitioning methods. Therefore, this article focuses on the above issues and takes the helical gear pair of a pure electric vehicle’s secondary reducer as the research object. A dynamic model of the helical gear transmission system is established to explore the effects of changes in tooth width and the number of grids in the involute direction on the maximum tooth surface contact stress, peak to peak transmission error, and simulation reliability of tooth surface contact spots at high and low speeds. This provides a reference for related research such as helical gear modification and simulation calculation.
By studying the influence of changes in the number of grids along the tooth width and involute direction of helical gears on the simulation accuracy of maximum tooth surface contact stress, peak to peak transmission error, and the distribution of tooth surface contact spots, the following conclusions can be drawn.
1) The maximum tooth surface contact stress, peak to peak transmission error, and simulation accuracy of tooth surface contact spot distribution of helical gears are not sensitive to changes in the number of grids in the involute direction. Under the same number of grids along the tooth width direction, the simulation values of maximum tooth surface contact stress and peak to peak transmission error show dynamic fluctuations with the increase of the number of grids in the involute direction, while the simulation results of tooth surface contact spot distribution do not show significant changes.
2) The simulation value of the maximum tooth surface contact stress of helical gears under high and low rotational speeds follows the same trend as the number of grids in the tooth width direction, both of which decrease first and then stabilize with the increase of the number of grids. The trend of the simulation value of peak to peak transmission error with the number of grids in the tooth width direction is opposite to that of the maximum tooth surface contact stress, which increases first and then stabilizes. When the number of grids along the tooth width direction exceeds 110, the maximum tooth surface contact stress and peak to peak transmission error no longer change as the number of grids further increases, and the number of grids reaches a saturated state.
3) The variation of the number of grids in the direction of helical gear tooth width has a certain impact on the simulation accuracy of tooth surface contact spot distribution. When the number of grids exceeds 80, the size distribution of tooth surface contact spots remains basically constant and no longer fluctuates significantly with the increase of the number of grids in the direction of tooth width.
4) The impact of changes in mesh quantity on the simulation accuracy of maximum tooth surface contact stress, peak to peak transmission error, and tooth surface contact spot distribution under high and low rotational speeds of helical gears is different. Compared with low rotational speed conditions, higher mesh quantity and quality are required at high rotational speeds to improve simulation reliability.