Optimization of Cabin Mounting System for Tractor using a Genetic Algorithm

Abstract

Abstract Purpose To analyze the behavior of a tractor cabin mounting system, a six-degrees-of-freedom (6-DOF) simulation model was developed, and a genetic algorithm was integrated into the model to optimize the design variables of the cabin mounting system. The performance and characteristics of the optimized cabin-mounting system were analyzed. Methods Eigenvalue analysis was performed using the developed model. Rigid-body mode decoupling theory was applied to optimize the design variables, and the energy decoupling method (EDM) was used to evaluate the degree of rigid-body mode decoupling. The design variables were optimized using NSGA-II genetic algorithm. Optimizations for two cases (Case #1: optimizing the stiffness and position of the mounts; Case#2: optimizing only the stiffness of the mounts) were conducted. Results energy decoupling rate (EDR) for Case #1 increased from 66.73% to 87.65%. As the position constraints relaxed, the mounts tended to move upwards and were widely distributed widely. EDR for Case #2 increased from 66.73% to 84.41%. In both cases, the mount stiffness decreased. Conclusions The EDR of the cabin mounting system was significantly improved due to optimization, and the rigid body mode frequencies were optimized within the target range.