摘要
基于齿轮摩擦加载接触分析(FLTCA)方法,提出了摆线准双曲面齿轮啮合效率优化设计方法。首先,通过预设空载传动误差峰峰值和接触区位置,实现了对摆线准双曲面齿轮正、反车齿面的修形设计。然后基于修形面设计,以行驶工况下齿轮啮合效率最大为优化目标,并综合考虑齿轮副加载传动误差峰峰值、双侧齿面满载接触印迹分布以及最大接触应力建立了优化分析模型。为了提高优化模型的求解速度,采用Kriging代理模型结合多岛遗传算法对优化模型进行了求解。最后,对某型号商用驱动桥摆线准双曲面齿轮副进行了实例设计和试验验证,通过空载接触印迹试验和整桥传动效率试验验证了所提优化方法的有效性。
Based on the gear friction loaded tooth contact analysis(FLTCA)method,an optimal design method was proposed for the meshing efficiency of face-hobbed hypoid gears.Firstly,a method was employed to preset the peak-to-peak values of unloaded transmission errors and the positions of the contact zones,facilitating the modification design of the positive and negative tooth surfaces of face-hobbed hypoid gears.Then,building upon the modified tooth surface design,an optimization objective was set to maximize gear meshing efficiency under driving conditions.And the optimization analysis model was established by comprehensively considering factors such as the peak-to-peak values of gear pair loaded transmission errors,distribution of full-load contact pattern on both sides of the tooth surfaces and the maximum contact stresses.To enhance the solution speed of the optimization model,the Kriging surrogate model was employed in conjunction with a multi-island genetic algorithm to address and solve the optimization model.Finally,a case design and test validation were conducted on a commercial drive axle with a face-hobbed hypoid gear pair.The effectivenesses of the optimization method proposed were verified through unloaded contact pattern tests and whole-axle transmission efficiency tests.
作者
王钦
贺迪
薛建华
彭金
范子杰
WANG Qin;HE Di;XUE Jianhua;PENG Jin;FAN Zijie(State Key Laboratory of Automotive Safety and Energy,Tsinghua University,Beijing,100084;Shaanxi Hande Axle Co.,Ltd.,Xi an,710201;Hande Axle(Zhuzhou)Gear Co.,Ltd.,Zhuzhou,Hunan,412000)
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2024年第11期1920-1927,1937,共9页
China Mechanical Engineering
基金
清华大学校企合作项目(20192002040)。
关键词
驱动桥
摆线准双曲面齿轮
接触分析
啮合效率
优化
drive axle
face-bobbed hypoid gear
tooth contact analysis
meshing efficiency
optimization