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作 者:杨秀建[1] 余间溪 张生斌 吴相稷 YANG Xiu-jian;YU Jian-xi;ZHANG Sheng-bin;WU Xiang-ji(School of Transportation Engineering,Kunming University of Science and Technology,Yunnan Kunming 650500,China)
机构地区:[1]昆明理工大学交通工程学院,云南昆明650500
出 处:《机械设计与制造》2024年第8期287-293,共7页Machinery Design & Manufacture
基 金:国家自然科学基金项目(51465023)。
摘 要:为研究液罐车防波板对液体纵向晃动及车辆动力学的影响,进行液罐车的液体纵向晃动受力预测及动力学分析。首先基于计算流体力学(CFD)软件FLUENT对罐体施加纵向加速度激励,获得不同充液率下有无防波板的液体纵向晃动力和晃动力矩。利用仿真数据,训练得到有无防波板的罐内液体纵向晃动Elman神经网络预测模型,以此建立一个简化的双轴液罐车整车纵向动力学模型。通过模型直线制动工况的仿真,考察防波板不同布置方式下制动距离的响应。结果表明:Elman神经网络预测模型可以有效地预测有无防波板的罐体受力;罐体内设置防波板可以减小车辆制动距离,且防波板两头小(等间距)中间大的布置方式的制动距离较小,有利于液罐车的纵向制动稳定性。In order to study the influence of baffles on liquid longitudinal sloshing and vehicle dynamics of liquid tanker,the liquid longitudinal sloshing force prediction and dynamics analysis were carried out.Firstly,the longitudinal acceleration excitation was applied to the tank based on the computational fluid dynamics(CFD)software FLUENT to obtain the longitudinal slosh force and slosh moment of the liquid in the tank with or without baffles at different filling rates.Based on the simulation data,the prediction model of longitudinal sloshing of liquid in tank with or without baffles was trained by Elman neural network,and a simplified longitudinal dynamics model of a biaxial liquid tanker was established.Through the simulation of linear braking condition,the responses of braking distances under different arrangements of baffles are investigated.The results show that the El‐man neural network prediction model can effectively predict the force of the tank with or without the baffles.The tank with baffles can reduce the braking distance of the vehicle and the arrangement of the baffles with small two ends(equal spacing)and large middle has a smaller braking distance,which is conducive to the longitudinal braking stability of the liquid tanker.
关 键 词:液罐车 CFD ELMAN神经网络 液体晃动模型 防波板
分 类 号:TH16[机械工程—机械制造及自动化] U469.61[机械工程—车辆工程]
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