首页|基于粒子群算法的农用轮胎柔性环模型参数辨识方法

基于粒子群算法的农用轮胎柔性环模型参数辨识方法

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  • 国家科技期刊平台
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轮胎柔性环模型能准确表达轮胎变形,但模型的刚度参数无法直接测定,因此模型刚度参数的辨识成为建模过程中的关键.本文基于轮胎柔性环模型运动学方程,分析农用轮胎固有频率与刚度参数之间的关系,提出基于粒子群算法的柔性环模型刚度参数辨识方法.通过轮胎模态试验获取轮胎固有频率,采用粒子群算法对柔性环模型刚度参数进行辨识.将固有频率的试验值与预测值的平均误差作为评价指标,对比粒子群算法与传统算法及遗传算法辨识结果,结果表明粒子群算法的参数辨识结果精度较高,平均绝对误差为1.67 Hz,平均相对误差为1.66％,相较于遗传算法,平均相对误差降低16.16％,运算时间减少93.19％.通过接地印痕试验获取农用轮胎接地角度,结合辨识所得刚度参数,估算轮胎所受到的垂向力,对比垂向力的试验值与预测值,结果表明粒子群算法的参数辨识结果精度较高,垂向载荷估算平均相对误差为1.97％,相对于遗传算法,平均相对误差降低12.05％.
Parameter Identification Method for Agricultural Tire Flexible Ring Model Based on Particle Swarm Optimization Algorithm
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.

agricultural tireflexible ring modelparticle swarm optimization algorithmmodal testingparameter identificationgenetic algorithm

孙瑞、王亚东、李怡宁、何志祝、朱忠祥、李臻

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中国农业大学工学院,北京 100083

智能农业动力装备全国重点实验室,北京 100083

贵州轮胎股份有限公司技术中心,贵阳 550201

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

国家重点研发计划青年科学家项目国家自然科学基金面上项目拼多多-中国农业大学研究基金项目

2022YFD200030052175259PC2023B01005

2024

10.6041/j.issn.1000-1298.2024.04.040

农业机械学报
中国农业机械学会 中国农业机械化科学研究院

农业机械学报

CSTPCD北大核心
影响因子：1.904
ISSN：1000-1298
年,卷(期)：2024.55(4)
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