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汽车悬架参数优化的仿真研究

Parametric Optimization of Automobile Suspension
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摘要 以BP神经网络对减振器的外特性进行建模为基础,Matlab/Simulink为工具,对汽车八自由度模型进行了平顺性仿真建模,并对含有不同神经网络减振器模型的整车振动响应输出进行了对比分析,从而找到适宜新车型的减振器,实现了汽车悬架阻尼参数的优化。 An Damper model of BP neural network and the eight degree-of-freedom simulation model for vehicle ride performance are developed by Matlab/Simulink toolbox. After analysis on the rules of ride performance when different Damper's neural network models are put into the vehicle simulation model, the most fitful shock absorber for new vehicle is found, the damping parameters are optimized.
机构地区 辽宁工业大学
出处 《拖拉机与农用运输车》 2009年第1期11-13,共3页 Tractor & Farm Transporter
关键词 神经网络 仿真 减振器 Neural network Simulation Shock absorber
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二级参考文献10

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