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主动悬架LQG控制及其液压参数研究 被引量:3

The research on LQG control of active suspension and its hydraulic parameters
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摘要 针对忽略作动器实际动作及液压系统参数造成目前的主动悬架模型精确性低的缺陷,结合液压原理,建立包含液压系统参数在内的主动悬架模型。通过分析LQG控制的原理及优点,确定车身加速度、悬架动挠度、车轮动位移的加权系数矩阵,以实现主动悬架的LQG控制。将SIMULINK仿真结果与被动悬架、主动悬架PID控制进行对比,并通过LQG控制模型及被动悬架模型,对系统进行频域分析。以LQG控制仿真试验为基础,对主动悬架耗能进行了研究。结果表明,包括液压系统参数在内的主动悬架LQG控制优化了传统主动悬架模型,车身加速度及车轮动位移参数较PID控制降低了40%以上,可提高车辆的操纵稳定性和乘坐舒适性,特别是在系统的一阶固有频率处,拥有更好的减振效果。能耗仿真计算结果表明,选用衔铁质量小、衔铁组件刚度小的比例电磁铁,可以有效降低系统耗能30%以上,但减振效果会有所降低。 For the low accuracy of current active suspension model caused by the neglect of actuator motion and hydraulic parameters,the active suspension model including the hydraulic parameters is built through combining the principle of hydraulic system.By analyzing the theory and advantages of LQG control,the weighting coefficient matrix of car body acceleration,suspension dynamic deflection,and tyre displacement is determined to realize the LQG control of the active suspension.The simulation results are compared with passive suspension and PID control of active suspension,and the frequency-domain analyses are conducted using the LQG control model and passive suspension model.The energy dissipation is studied based on the LQG control test.The results show that the LQG control of active suspension including the hydraulic parameters optimizes the ordinary active suspension model and improves the riding comfort and control stability.The car body acceleration and the tyre dynamic displacement can be reduced over 40%compared with PID control.Better vibration damping effects can be reached in the system especially with the first-order natural frequency.The energy dissipation simulation results indicate that the energy can be reduced by 30% or more if the electromagnetic valve with low stiffness and mass ratio is used,while the vibration damping effects will also be reduced.
出处 《中国科技论文》 北大核心 2017年第16期1841-1847,共7页 China Sciencepaper
基金 高等学校博士学科点专项科研基金资助项目(20110205110008)
关键词 车辆工程 主动悬架 液压系统模型 LQG控制 能耗分析 vehicle engineering active suspension hydraulic system model LQG control energy dissipation analysis
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