Abstract:

To tackle the challenges of drive component selection in electric cylinder lifting servo mechanisms with nonlinear dynamics characteristics， an efficient selection method of drive components was proposed based on peak parameter matching. The analytical formulae for the mechanism's inertial torque， Coriolis torque， unbalanced torque， frictional torque， and environmental loads were obtained via Lagrange dynamics， explicitly revealing the computational complexity involved. Then， leveraging peak external loads and mechanism arm lengths， along with the system's nonlinear characteristics， an efficient selection approach was formulated. Finally， the application constraints were established based on the load-to-drive mass ratio， when the mechanism's load-to-drive ratio exceeded the critical value， the method might be applied. Simulation results demonstrate that based on the time and spatial complexity，the computational efficiency of the efficient selection method is 1629 times that of the conventional method under a sampling step of 0.01 rad. Experimental results confirm that the electric cylinder lifting servo mechanism's load-to-drive ratio is as 15.37， which is greater than the critical value of 11.68， achieving 1 rad/s² acceleration under sinusoidal instructions and 0.785 rad/s velocity under step instructions.

Key words: lifting mechanism, drive component, peak parameter matching, time and spatial complexity

摘要：

为解决电动缸举升伺服机构非线性动力学特性下驱动部件选型困难的问题，提出一种基于峰值参数匹配的驱动部件高效选型方法。采用拉格朗日动力学方程推导了机构的惯性力矩、科氏力矩、不平衡力矩、摩擦力矩及环境载荷的解析式，明确了求解的复杂性；然后，基于外部载荷峰值和机构力臂峰值，以及电动缸举升伺服机构的非线性动力学特性，推导了机构驱动部件的高效选型方法；最后，推导了该方法基于负载质量与驱动部件质量的比值的应用约束条件，即当机构载驱比超过临界值时可采用该方法。仿真结果表明，基于时间与空间复杂度，在0.01 rad采样步长下高效选型方法的计算效率是常规方法的1629倍。实验结果表明，电动缸举升伺服机构的载驱比为15.37，大于临界值11.68，在正弦指令下加速度达预设值1 rad/s²，在阶跃指令下速度达预设值0.785 rad/s。

关键词: 举升机构, 驱动部件, 峰值参数匹配, 时间与空间复杂度