Optimization and Modeling of a Spatial CAM Mechanism for a Two-Dimensional Plunger Electro-Hydraulic Pump

Abstract

Traditional cam movements in piston pumps follow a non-stopping motion law, resulting in insufficient smoothness in plunger stroke changes. Consequently, this directly impacts the theoretical flow rate of the pump. To address this issue, describes the transition curve of the non-stopping motion law is constructed in this study by using a fivefold B-spline curve. The maximum uncaused velocity and acceleration are considered optimization parameters. Multi-objective optimization of the motion law is conducted using a genetic algorithm, resulting in the generation of a Pareto solution set. Compared to the modified equivalent acceleration (MEA) motion law, the B-spline combined motion law leads to a reduction of 1.39% and 0.86% in the maximum velocity and acceleration characteristic values, respectively. Furthermore, by employing the principle of a single-parameter surface envelope, a mathematical model of the cam surface is developed. The obtained data points are then solved using the double-three times Bspline cam surface interpolation algorithm. Subsequently, the interpolation result is translated into a cam surface model file based on the data structure of the IGES file.The optimization results demonstrate that compared to equal acceleration and deceleration motion laws, the B-spline optimization curve achieves a seamless transition. Specifically, the maximum pressure angle decreases from 27.98°to 19.92°, and the minimum radius of curvature decreases from 9.94 mm to 7.44 mm, validating the accuracy of the theoretical analysis. Experimental displacement tests are conducted on the spatial cam mechanism, revealing that the cam design process has been streamlined, and the designed spatial cam exhibits enhanced fitting performance.INDEX TERMS Space CAM mechanism; two-dimensional plunger electro-hydraulic pump; B-spline curve; multi-objective genetic algorithm; envelope principle of a single-parameter surface