农业机械学报2024，Vol.55Issue(4)：402-410,9.DOI:10.6041/j.issn.1000-1298.2024.04.040
基于粒子群算法的农用轮胎柔性环模型参数辨识方法
Parameter Identification Method for Agricultural Tire Flexible Ring Model Based on Particle Swarm Optimization Algorithm
摘要
Abstract
The tire flexible ring model can accurately express tire deformation,but the stiffness parameters of the model cannot be directly measured,so identifying the stiffness parameters of the model becomes the key in the modeling process.Based on the kinematic equation of the tire flexible ring model,the relationship between the natural frequency and stiffness parameters of agricultural tires was analyzed,and a method for identifying the stiffness parameters of the flexible ring model was proposed based on particle swarm optimization(PSO)algorithm.Based on the kinematics equation of the flexible ring model tire,the relationship between the natural frequency and the stiffness parameters of the agricultural tire was analyzed,and a method for identifying the stiffness parameter of agricultural tire flexible ring model based on PSO algorithm was proposed.A tire testing platform was built,the natural frequency was obtained through tire modal testing,and PSO algorithm was used to identify the stiffness parameters of the flexible ring model.Using the average error between the experimental and predicted values of the natural frequency as the evaluation index,the identification results of PSO algorithm were compared with traditional methods and genetic algorithm(GA).The results showed that PSO algorithm had the highest accuracy,with an average absolute error of 1.67 Hz and an average relative error of 1.66％.Compared with GA,the average relative error was decreased by 16.16％and the computation time was decreased by 93.19％.The correctness and accuracy of the stiffness parameter identification method was proved based on PSO algorithm.The grounding angle of agricultural tires was obtained through the contact patch test,and the vertical force on the tires was estimated based on the identified stiffness parameters.The experimental and predicted values of vertical force were compared,and the results showed that the parameter identification results obtained by the particle swarm algorithm had the highest accuracy.The average relative error of vertical load estimation was 1.97％,which was reduced by 12.05％compared with the genetic algorithm.关键词
农用轮胎/柔性环模型/粒子群算法/模态试验/参数辨识/遗传算法Key words
agricultural tire/flexible ring model/particle swarm optimization algorithm/modal testing/parameter identification/genetic algorithm分类
交通工程引用本文复制引用
孙瑞,王亚东,李怡宁,何志祝,朱忠祥,李臻..基于粒子群算法的农用轮胎柔性环模型参数辨识方法[J].农业机械学报,2024,55(4):402-410,9.基金项目
国家重点研发计划青年科学家项目(2022YFD2000300)、国家自然科学基金面上项目(52175259)和拼多多-中国农业大学研究基金项目(PC2023B01005) （2022YFD2000300）
